Systems and methods for analyzing network metrics

ABSTRACT

The present solution is directed to systems and methods for providing, by a device intermediary to a plurality of clients and one or more servers, analytics on a stream of network packets traversing the device. The systems and methods include the device identifying, while the device manages network traffic between the plurality of clients and the one or more servers, a stream of network packets, from a plurality of streams of network packets of the network traffic traversing the device, corresponding to a flow identifier, e.g., a selected one of an internet protocol address, a uniform resource locator or an application identifier. The systems and methods may include a collector of the analytics engine collecting, while the device manages network traffic, metrics on the identified stream of network packets and generating one or more stream objects that comprise the collected metrics.

RELATED APPLICATIONS

The present application claims the benefit of and priority to U.S.Provisional Patent Application No. 61/489,521 entitled “Systems andMethods for Analyzing Network Metrics” and filed on May 24, 2011, whichis hereby incorporated by reference in its entirety for all purposes.

FIELD OF THE DISCLOSURE

The present application generally relates to data communicationnetworks. In particular, the present application relates to systems andmethods for analyzing network traffic by the same intermediary devicemanaging network traffic between clients and servers.

BACKGROUND OF THE DISCLOSURE

End users obtain great insight into network operations by using networkanalytics to analyze and understand network metrics. In particular,network analytics can be used to quantify an end-user's experienceinteracting with a network. Network analytics can also be used totroubleshoot network problems, plan for network capacity, monitorapplications and intelligently implement business strategies.Accomplishing these tasks can include using a network analytics systemto do the following: collect network information; analyze networkinformation; and report application data.

In many ways, implementing a network analytics solution within aheterogeneous network environment can be difficult. Endpoints of anetwork are often not the same device and out-of-band devices can createnetwork topology challenges. Existing analytics solutions compriseproducts that do not scale to large and small network configurations.Scaling existing solutions to different network configurations can becostly and introduce inefficiencies into the system. Furthermore,challenges are posed by encrypted traffic that present the need tomanage certifications and encryption keys often issued from a range ofsecurity schemes.

SUMMARY OF THE DISCLOSURE

In some aspects, the present solution is directed to methods forproviding, by a device intermediary to a plurality of clients and one ormore servers, analytics on a stream of network packets traversing thedevice while managing network traffic between the plurality of clientsand the one or more servers. The methods generally include identifying,by the device while managing network traffic between the plurality ofclients and the one or more servers, a stream of network packets from aplurality of streams of network packets of the network traffictraversing the device and corresponding to a flow identifier. The flowidentifier may be selected from one of: an internet protocol (IP)address, a uniform resource locator (URL), and an applicationidentifier. The methods generally include collecting, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, metrics on the identified stream of network packetsand generating one or more stream objects that comprise the collectedmetrics.

In some applications of these methods, the methods may includereceiving, by the device while managing network traffic between theplurality of clients and the one or more servers, a selection from auser of one of the IP address, the URL, or the application to analyzeone or more metrics. The methods may include collecting, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, a plurality of the following metrics: bandwidthutilization, a number of requests, a number of connections and responsetime. The methods may include collecting, by the device while managingnetwork traffic between the plurality of clients and the one or moreservers, for the identified stream of network packets, a frequency atwhich requests are made.

In some applications of these methods, the methods may include storing,by the device while managing network traffic between the plurality ofclients and the one or more servers, to the one or more streams objects,a number of requests issued by the one or more clients via theidentified stream of network packets. The methods may include storing,by the device while managing network traffic between the plurality ofclients and the one or more servers, to the one or more streams objects,a number of requests issued by the one or more clients via theidentified stream of network packets. The methods may include storing,by the device while managing network traffic between the plurality ofclients and the one or more servers, to the one or more streams objects,a number of transport layer connections used by the identified stream ofnetwork packets. The methods may include storing, by the device whilemanaging network traffic between the plurality of clients and the one ormore servers, to the one or more streams objects, an amount of bandwidthused by the selected one of the IP address, the URL, or the applicationvia the identified stream of network packets.

In some applications of these methods, the methods may includeproviding, by the device while managing network traffic between theplurality of clients and the one or more servers, data from the one ormore streamed objects for displaying metrics for the identified streamof network packets. The methods may include collecting, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, for the identified stream of network packets datafor a custom variable and storing the data for the custom variable tothe one or more streamed objects.

In some aspects, the present solution is directed to systems forproviding, by a device intermediary to a plurality of clients and one ormore servers, analytics on a stream of network packets traversing thedevice while managing network traffic between the plurality of clientsand the one or more servers. The systems include a device intermediaryto a plurality of clients and one or more servers and an analyticsengine executing on the device identifying, while the device managesnetwork traffic between the plurality of clients and the one or moreservers, a stream of network packets from a plurality of streams ofnetwork packets of the network traffic traversing the devicecorresponding to a flow identifier. The systems may include identifyinga stream of packets corresponding to a selected one of an internetprotocol (IP) address, a uniform resource locator (URL) or anapplication identifier. The systems may include a collector of theanalytics engine collecting, while the device manages network trafficbetween the plurality of clients and the one or more servers, metrics onthe identified stream of network packets.

In some embodiments, the analytics engine, while the device managesnetwork traffic between the plurality of clients and the one or moreservers, generates one or more stream objects that comprise thecollected metrics. In some embodiments of the systems, the devicereceives, while managing network traffic between the plurality ofclients and the one or more servers, a selection from a user of one ofthe IP address, the URL, or the application to analyze one or moremetrics.

In some embodiments of the systems, the collector, while the devicemanages network traffic between the plurality of clients and the one ormore servers, collects a plurality of the following metrics: bandwidthutilization, a number of requests, a number of connections and responsetime. In some embodiments of the systems, the collector, while thedevice manages g network traffic between the plurality of clients andthe one or more servers, for the identified stream of network packets,collects a frequency at which requests are made.

In some embodiments of the systems, the analytics engine stores, whilethe device manages network traffic between the plurality of clients andthe one or more servers, to the one or more streams objects, a number ofrequests issued by the one or more clients via the identified stream ofnetwork packets. In some embodiments of the systems, the analyticsengine stores, while the device manages network traffic between theplurality of clients and the one or more servers, to the one or morestreams objects, a number of requests issued by the one or more clientsvia the identified stream of network packets. In some embodiments of thesystems, the analytics engine stores, while the device manages networktraffic between the plurality of clients and the one or more servers, tothe one or more streams objects a number of transport layer connectionsused by the identified stream of network packets. In some embodiments ofthe systems, the analytics engine stores, while the device managesnetwork traffic between the plurality of clients and the one or moreservers, to the one or more streams objects, an amount of bandwidth usedby the selected one of the IP address, the URL, or the application viathe identified stream of network packets.

In some embodiments of the systems, the analytics engine provides, whilethe device manages the device while managing network traffic between theplurality of clients and the one or more servers, data from the one ormore streamed objects for displaying metrics for the identified streamof network packets. In some embodiments of the systems, the collectorcollects, while the device manages network traffic between the pluralityof clients and the one or more servers, for the identified stream ofnetwork packets data for a custom variable and the analytics enginestores the data for the custom variable to the one or more streamedobjects.

Implementing methods and systems for deploying a network analyzer caninclude using a preexisting load-balancer to implement the networkanalytics system. The preexisting load balancer can perform any of thefollowing functions: remove network inefficiencies; accelerate thetransmission of data over the network; secure and protect data as it istransmitted across the network; and be flexible enough to obtain andanalyze any number of metrics. The load balancer, in some embodiments,can be a CITRIX SYSTEMS NETSCALER. This load balancer can remove networkinefficiencies by using an inline device, e.g. NetScaler, to do CMP, SSLand server offloading. The load balancer can also accelerate thetransmission of data by having deep application insight. The loadbalancer can also secure and protect information transmitted over thenetwork by executing all applications and logic on bare metal.Furthermore, the load balancer can be flexible because it has a richstatistics infrastructure like an expressive policy engine. Usingexisting hardware to implement a network analytics solution can takeadvantage of an existing hardware footprint and can be used to highlighttrends and outliers while being used to troubleshoot problems.

The details of various embodiments of the invention are set forth in theaccompanying drawings and the description below.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and other objects, aspects, features, and advantages ofthe disclosure will become more apparent and better understood byreferring to the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1A is a block diagram of an embodiment of a network environment fora client to access a server via an appliance;

FIG. 1B is a block diagram of an embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIG. 1C is a block diagram of another embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIG. 1D is a block diagram of another embodiment of an environment fordelivering a computing environment from a server to a client via anappliance;

FIGS. 1E-1H are block diagrams of embodiments of a computing device;

FIG. 2A is a block diagram of an embodiment of an appliance forprocessing communications between a client and a server;

FIG. 2B is a block diagram of another embodiment of an appliance foroptimizing, accelerating, load-balancing and routing communicationsbetween a client and a server;

FIG. 3 is a block diagram of an embodiment of a client for communicatingwith a server via the appliance;

FIG. 4A is a block diagram of an embodiment of a virtualizationenvironment;

FIG. 4B is a block diagram of another embodiment of a virtualizationenvironment;

FIG. 4C is a block diagram of an embodiment of a virtualized appliance;

FIG. 5A are block diagrams of embodiments of approaches to implementingparallelism in a multi-core system;

FIG. 5B is a block diagram of an embodiment of a system utilizing amulti-core system;

FIG. 5C is a block diagram of another embodiment of an aspect of amulti-core system;

FIG. 6A is a block diagram of an embodiment of an intermediary device toa plurality of clients and one or more servers providing network trafficanalytics;

FIG. 6B is a flow diagram of an embodiment of a method of providinganalytics on a stream of network packets while managing network trafficbetween a plurality of clients and one or more servers; and

FIGS. 7A-7E are embodiments of pictorial representation of variousnetwork metrics provided by the systems and methods of FIGS. 6A and 6B.

The features and advantages of the present disclosure will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings, in which like reference charactersidentify corresponding elements throughout. In the drawings, likereference numbers generally indicate identical, functionally similar,and/or structurally similar elements.

DETAILED DESCRIPTION OF THE DISCLOSURE

For purposes of reading the description of the various embodimentsbelow, the following descriptions of the sections of the specificationand their respective contents may be helpful:

-   -   Section A describes a network environment and computing        environment which may be useful for practicing embodiments        described herein;    -   Section B describes embodiments of systems and methods for        delivering a computing environment to a remote user;    -   Section C describes embodiments of systems and methods for        accelerating communications between a client and a server;    -   Section D describes embodiments of systems and methods for        virtualizing an application delivery controller;    -   Section E describes embodiments of systems and methods for        providing a multi-core architecture and environment; and    -   Section F describes embodiments of systems and methods for        providing analytics via an intermediary device.

A. Network and Computing Environment

Prior to discussing the specifics of embodiments of the systems andmethods of a cloud bridge, it may be helpful to discuss the network andcomputing environments in which such embodiments may be deployed.Referring now to FIG. 1A, an embodiment of a network environment isdepicted. In brief overview, the network environment comprises one ormore clients 102 a-102 n (also generally referred to as local machine(s)102, or client(s) 102) in communication with one or more servers 106a-106 n (also generally referred to as server(s) 106, or remotemachine(s) 106) via one or more networks 104, 104′ (generally referredto as network 104). In some embodiments, a client 102 communicates witha server 106 via an appliance 200.

Although FIG. 1A shows a network 104 and a network 104′ between theclients 102 and the servers 106, the clients 102 and the servers 106 maybe on the same network 104. The networks 104 and 104′ can be the sametype of network or different types of networks. The network 104 and/orthe network 104′ can be a local-area network (LAN), such as a companyIntranet, a metropolitan area network (MAN), or a wide area network(WAN), such as the Internet or the World Wide Web. In one embodiment,network 104′ may be a private network and network 104 may be a publicnetwork. In some embodiments, network 104 may be a private network andnetwork 104′ a public network. In another embodiment, networks 104 and104′ may both be private networks. In some embodiments, clients 102 maybe located at a branch office of a corporate enterprise communicatingvia a WAN connection over the network 104 to the servers 106 located ata corporate data center.

The network 104 and/or 104′ be any type and/or form of network and mayinclude any of the following: a point to point network, a broadcastnetwork, a wide area network, a local area network, a telecommunicationsnetwork, a data communication network, a computer network, an ATM(Asynchronous Transfer Mode) network, a SONET (Synchronous OpticalNetwork) network, a SDH (Synchronous Digital Hierarchy) network, awireless network and a wireline network. In some embodiments, thenetwork 104 may comprise a wireless link, such as an infrared channel orsatellite band. The topology of the network 104 and/or 104′ may be abus, star, or ring network topology. The network 104 and/or 104′ andnetwork topology may be of any such network or network topology as knownto those ordinarily skilled in the art capable of supporting theoperations described herein.

As shown in FIG. 1A, the appliance 200, which also may be referred to asan interface unit 200 or gateway 200, is shown between the networks 104and 104′. In some embodiments, the appliance 200 may be located onnetwork 104. For example, a branch office of a corporate enterprise maydeploy an appliance 200 at the branch office. In other embodiments, theappliance 200 may be located on network 104′. For example, an appliance200 may be located at a corporate data center. In yet anotherembodiment, a plurality of appliances 200 may be deployed on network104. In some embodiments, a plurality of appliances 200 may be deployedon network 104′. In one embodiment, a first appliance 200 communicateswith a second appliance 200′. In other embodiments, the appliance 200could be a part of any client 102 or server 106 on the same or differentnetwork 104,104′ as the client 102. One or more appliances 200 may belocated at any point in the network or network communications pathbetween a client 102 and a server 106.

In some embodiments, the appliance 200 comprises any of the networkdevices manufactured by Citrix Systems, Inc. of Ft. Lauderdale Fla.,referred to as Citrix NetScaler devices. In other embodiments, theappliance 200 includes any of the product embodiments referred to asWebAccelerator and BigIP manufactured by F5 Networks, Inc. of Seattle,Wash. In another embodiment, the appliance 205 includes any of the DXacceleration device platforms and/or the SSL VPN series of devices, suchas SA 700, SA 2000, SA 4000, and SA 6000 devices manufactured by JuniperNetworks, Inc. of Sunnyvale, Calif. In yet another embodiment, theappliance 200 includes any application acceleration and/or securityrelated appliances and/or software manufactured by Cisco Systems, Inc.of San Jose, Calif., such as the Cisco ACE Application Control EngineModule service software and network modules, and Cisco AVS SeriesApplication Velocity System.

In one embodiment, the system may include multiple, logically-groupedservers 106. In these embodiments, the logical group of servers may bereferred to as a server farm 38. In some of these embodiments, theserves 106 may be geographically dispersed. In some cases, a farm 38 maybe administered as a single entity. In other embodiments, the serverfarm 38 comprises a plurality of server farms 38. In one embodiment, theserver farm executes one or more applications on behalf of one or moreclients 102.

The servers 106 within each farm 38 can be heterogeneous. One or more ofthe servers 106 can operate according to one type of operating systemplatform (e.g., WINDOWS NT, manufactured by Microsoft Corp. of Redmond,Wash.), while one or more of the other servers 106 can operate onaccording to another type of operating system platform (e.g., Unix orLinux). The servers 106 of each farm 38 do not need to be physicallyproximate to another server 106 in the same farm 38. Thus, the group ofservers 106 logically grouped as a farm 38 may be interconnected using awide-area network (WAN) connection or medium-area network (MAN)connection. For example, a farm 38 may include servers 106 physicallylocated in different continents or different regions of a continent,country, state, city, campus, or room. Data transmission speeds betweenservers 106 in the farm 38 can be increased if the servers 106 areconnected using a local-area network (LAN) connection or some form ofdirect connection.

Servers 106 may be referred to as a file server, application server, webserver, proxy server, or gateway server. In some embodiments, a server106 may have the capacity to function as either an application server oras a master application server. In one embodiment, a server 106 mayinclude an Active Directory. The clients 102 may also be referred to asclient nodes or endpoints. In some embodiments, a client 102 has thecapacity to function as both a client node seeking access toapplications on a server and as an application server providing accessto hosted applications for other clients 102 a-102 n.

In some embodiments, a client 102 communicates with a server 106. In oneembodiment, the client 102 communicates directly with one of the servers106 in a farm 38. In another embodiment, the client 102 executes aprogram neighborhood application to communicate with a server 106 in afarm 38. In still another embodiment, the server 106 provides thefunctionality of a master node. In some embodiments, the client 102communicates with the server 106 in the farm 38 through a network 104.Over the network 104, the client 102 can, for example, request executionof various applications hosted by the servers 106 a-106 n in the farm 38and receive output of the results of the application execution fordisplay. In some embodiments, only the master node provides thefunctionality required to identify and provide address informationassociated with a server 106′ hosting a requested application.

In one embodiment, the server 106 provides functionality of a webserver. In another embodiment, the server 106 a receives requests fromthe client 102, forwards the requests to a second server 106 b andresponds to the request by the client 102 with a response to the requestfrom the server 106 b. In still another embodiment, the server 106acquires an enumeration of applications available to the client 102 andaddress information associated with a server 106 hosting an applicationidentified by the enumeration of applications. In yet anotherembodiment, the server 106 presents the response to the request to theclient 102 using a web interface. In one embodiment, the client 102communicates directly with the server 106 to access the identifiedapplication. In another embodiment, the client 102 receives applicationoutput data, such as display data, generated by an execution of theidentified application on the server 106.

Referring now to FIG. 1B, an embodiment of a network environmentdeploying multiple appliances 200 is depicted. A first appliance 200 maybe deployed on a first network 104 and a second appliance 200′ on asecond network 104′. For example a corporate enterprise may deploy afirst appliance 200 at a branch office and a second appliance 200′ at adata center. In another embodiment, the first appliance 200 and secondappliance 200′ are deployed on the same network 104 or network 104. Forexample, a first appliance 200 may be deployed for a first server farm38, and a second appliance 200 may be deployed for a second server farm38′. In another example, a first appliance 200 may be deployed at afirst branch office while the second appliance 200′ is deployed at asecond branch office′. In some embodiments, the first appliance 200 andsecond appliance 200′ work in cooperation or in conjunction with eachother to accelerate network traffic or the delivery of application anddata between a client and a server.

Referring now to FIG. 1C, another embodiment of a network environmentdeploying the appliance 200 with one or more other types of appliances,such as between one or more WAN optimization appliance 205, 205′ isdepicted. For example a first WAN optimization appliance 205 is shownbetween networks 104 and 104′ and a second WAN optimization appliance205′ may be deployed between the appliance 200 and one or more servers106. By way of example, a corporate enterprise may deploy a first WANoptimization appliance 205 at a branch office and a second WANoptimization appliance 205′ at a data center. In some embodiments, theappliance 205 may be located on network 104′. In other embodiments, theappliance 205′ may be located on network 104. In some embodiments, theappliance 205′ may be located on network 104′ or network 104″. In oneembodiment, the appliance 205 and 205′ are on the same network. Inanother embodiment, the appliance 205 and 205′ are on differentnetworks. In another example, a first WAN optimization appliance 205 maybe deployed for a first server farm 38 and a second WAN optimizationappliance 205′ for a second server farm 38′.

In one embodiment, the appliance 205 is a device for accelerating,optimizing or otherwise improving the performance, operation, or qualityof service of any type and form of network traffic, such as traffic toand/or from a WAN connection. In some embodiments, the appliance 205 isa performance enhancing proxy. In other embodiments, the appliance 205is any type and form of WAN optimization or acceleration device,sometimes also referred to as a WAN optimization controller. In oneembodiment, the appliance 205 is any of the product embodiments referredto as WANScaler manufactured by Citrix Systems, Inc. of Ft. Lauderdale,Fla. In other embodiments, the appliance 205 includes any of the productembodiments referred to as BIG-IP link controller and WANjetmanufactured by F5 Networks, Inc. of Seattle, Wash. In anotherembodiment, the appliance 205 includes any of the WX and WXC WANacceleration device platforms manufactured by Juniper Networks, Inc. ofSunnyvale, Calif. In some embodiments, the appliance 205 includes any ofthe steelhead line of WAN optimization appliances manufactured byRiverbed Technology of San Francisco, Calif. In other embodiments, theappliance 205 includes any of the WAN related devices manufactured byExpand Networks Inc. of Roseland, N.J. In one embodiment, the appliance205 includes any of the WAN related appliances manufactured by PacketeerInc. of Cupertino, Calif., such as the PacketShaper, iShared, and SkyXproduct embodiments provided by Packeteer. In yet another embodiment,the appliance 205 includes any WAN related appliances and/or softwaremanufactured by Cisco Systems, Inc. of San Jose, Calif., such as theCisco Wide Area Network Application Services software and networkmodules, and Wide Area Network engine appliances.

In one embodiment, the appliance 205 provides application and dataacceleration services for branch-office or remote offices. In oneembodiment, the appliance 205 includes optimization of Wide Area FileServices (WAFS). In another embodiment, the appliance 205 acceleratesthe delivery of files, such as via the Common Internet File System(CIFS) protocol. In other embodiments, the appliance 205 providescaching in memory and/or storage to accelerate delivery of applicationsand data. In one embodiment, the appliance 205 provides compression ofnetwork traffic at any level of the network stack or at any protocol ornetwork layer. In another embodiment, the appliance 205 providestransport layer protocol optimizations, flow control, performanceenhancements or modifications and/or management to accelerate deliveryof applications and data over a WAN connection. For example, in oneembodiment, the appliance 205 provides Transport Control Protocol (TCP)optimizations. In other embodiments, the appliance 205 providesoptimizations, flow control, performance enhancements or modificationsand/or management for any session or application layer protocol.

In another embodiment, the appliance 205 encoded any type and form ofdata or information into custom or standard TCP and/or IP header fieldsor option fields of network packet to announce presence, functionalityor capability to another appliance 205′. In another embodiment, anappliance 205′ may communicate with another appliance 205′ using dataencoded in both TCP and/or IP header fields or options. For example, theappliance may use TCP option(s) or IP header fields or options tocommunicate one or more parameters to be used by the appliances 205,205′ in performing functionality, such as WAN acceleration, or forworking in conjunction with each other.

In some embodiments, the appliance 200 preserves any of the informationencoded in TCP and/or IP header and/or option fields communicatedbetween appliances 205 and 205′. For example, the appliance 200 mayterminate a transport layer connection traversing the appliance 200,such as a transport layer connection from between a client and a servertraversing appliances 205 and 205′. In one embodiment, the appliance 200identifies and preserves any encoded information in a transport layerpacket transmitted by a first appliance 205 via a first transport layerconnection and communicates a transport layer packet with the encodedinformation to a second appliance 205′ via a second transport layerconnection.

Referring now to FIG. 1D, a network environment for delivering and/oroperating a computing environment on a client 102 is depicted. In someembodiments, a server 106 includes an application delivery system 190for delivering a computing environment or an application and/or datafile to one or more clients 102. In brief overview, a client 10 is incommunication with a server 106 via network 104, 104′ and appliance 200.For example, the client 102 may reside in a remote office of a company,e.g., a branch office, and the server 106 may reside at a corporate datacenter. The client 102 comprises a client agent 120, and a computingenvironment 15. The computing environment 15 may execute or operate anapplication that accesses, processes or uses a data file. The computingenvironment 15, application and/or data file may be delivered via theappliance 200 and/or the server 106.

In some embodiments, the appliance 200 accelerates delivery of acomputing environment 15, or any portion thereof, to a client 102. Inone embodiment, the appliance 200 accelerates the delivery of thecomputing environment 15 by the application delivery system 190. Forexample, the embodiments described herein may be used to acceleratedelivery of a streaming application and data file processable by theapplication from a central corporate data center to a remote userlocation, such as a branch office of the company. In another embodiment,the appliance 200 accelerates transport layer traffic between a client102 and a server 106. The appliance 200 may provide accelerationtechniques for accelerating any transport layer payload from a server106 to a client 102, such as: 1) transport layer connection pooling, 2)transport layer connection multiplexing, 3) transport control protocolbuffering, 4) compression and 5) caching. In some embodiments, theappliance 200 provides load balancing of servers 106 in responding torequests from clients 102. In other embodiments, the appliance 200 actsas a proxy or access server to provide access to the one or more servers106. In another embodiment, the appliance 200 provides a secure virtualprivate network connection from a first network 104 of the client 102 tothe second network 104′ of the server 106, such as an SSL VPNconnection. It yet other embodiments, the appliance 200 providesapplication firewall security, control and management of the connectionand communications between a client 102 and a server 106.

In some embodiments, the application delivery management system 190provides application delivery techniques to deliver a computingenvironment to a desktop of a user, remote or otherwise, based on aplurality of execution methods and based on any authentication andauthorization policies applied via a policy engine 195. With thesetechniques, a remote user may obtain a computing environment and accessto server stored applications and data files from any network connecteddevice 100. In one embodiment, the application delivery system 190 mayreside or execute on a server 106. In another embodiment, theapplication delivery system 190 may reside or execute on a plurality ofservers 106 a-106 n. In some embodiments, the application deliverysystem 190 may execute in a server farm 38. In one embodiment, theserver 106 executing the application delivery system 190 may also storeor provide the application and data file. In another embodiment, a firstset of one or more servers 106 may execute the application deliverysystem 190, and a different server 106 n may store or provide theapplication and data file. In some embodiments, each of the applicationdelivery system 190, the application, and data file may reside or belocated on different servers. In yet another embodiment, any portion ofthe application delivery system 190 may reside, execute or be stored onor distributed to the appliance 200, or a plurality of appliances.

The client 102 may include a computing environment 15 for executing anapplication that uses or processes a data file. The client 102 vianetworks 104, 104′ and appliance 200 may request an application and datafile from the server 106. In one embodiment, the appliance 200 mayforward a request from the client 102 to the server 106. For example,the client 102 may not have the application and data file stored oraccessible locally. In response to the request, the application deliverysystem 190 and/or server 106 may deliver the application and data fileto the client 102. For example, in one embodiment, the server 106 maytransmit the application as an application stream to operate incomputing environment 15 on client 102.

In some embodiments, the application delivery system 190 comprises anyportion of the Citrix Access Suite™ by Citrix Systems, Inc., such as theMetaFrame or Citrix Presentation Server™ and/or any of the Microsoft®Windows Terminal Services manufactured by the Microsoft Corporation. Inone embodiment, the application delivery system 190 may deliver one ormore applications to clients 102 or users via a remote-display protocolor otherwise via remote-based or server-based computing. In anotherembodiment, the application delivery system 190 may deliver one or moreapplications to clients or users via steaming of the application.

In one embodiment, the application delivery system 190 includes a policyengine 195 for controlling and managing the access to, selection ofapplication execution methods and the delivery of applications. In someembodiments, the policy engine 195 determines the one or moreapplications a user or client 102 may access. In another embodiment, thepolicy engine 195 determines how the application should be delivered tothe user or client 102, e.g., the method of execution. In someembodiments, the application delivery system 190 provides a plurality ofdelivery techniques from which to select a method of applicationexecution, such as a server-based computing, streaming or delivering theapplication locally to the client 120 for local execution.

In one embodiment, a client 102 requests execution of an applicationprogram and the application delivery system 190 comprising a server 106selects a method of executing the application program. In someembodiments, the server 106 receives credentials from the client 102. Inanother embodiment, the server 106 receives a request for an enumerationof available applications from the client 102. In one embodiment, inresponse to the request or receipt of credentials, the applicationdelivery system 190 enumerates a plurality of application programsavailable to the client 102. The application delivery system 190receives a request to execute an enumerated application. The applicationdelivery system 190 selects one of a predetermined number of methods forexecuting the enumerated application, for example, responsive to apolicy of a policy engine. The application delivery system 190 mayselect a method of execution of the application enabling the client 102to receive application-output data generated by execution of theapplication program on a server 106. The application delivery system 190may select a method of execution of the application enabling the localmachine 10 to execute the application program locally after retrieving aplurality of application files comprising the application. In yetanother embodiment, the application delivery system 190 may select amethod of execution of the application to stream the application via thenetwork 104 to the client 102.

A client 102 may execute, operate or otherwise provide an application,which can be any type and/or form of software, program, or executableinstructions such as any type and/or form of web browser, web-basedclient, client-server application, a thin-client computing client, anActiveX control, or a Java applet, or any other type and/or form ofexecutable instructions capable of executing on client 102. In someembodiments, the application may be a server-based or a remote-basedapplication executed on behalf of the client 102 on a server 106. In oneembodiments the server 106 may display output to the client 102 usingany thin-client or remote-display protocol, such as the IndependentComputing Architecture (ICA) protocol manufactured by Citrix Systems,Inc. of Ft. Lauderdale, Fla. or the Remote Desktop Protocol (RDP)manufactured by the Microsoft Corporation of Redmond, Wash. Theapplication can use any type of protocol and it can be, for example, anHTTP client, an FTP client, an Oscar client, or a Telnet client. Inother embodiments, the application comprises any type of softwarerelated to VoIP communications, such as a soft IP telephone. In furtherembodiments, the application comprises any application related toreal-time data communications, such as applications for streaming videoand/or audio.

In some embodiments, the server 106 or a server farm 38 may be runningone or more applications, such as an application providing a thin-clientcomputing or remote display presentation application. In one embodiment,the server 106 or server farm 38 executes as an application, any portionof the Citrix Access Suite™ by Citrix Systems, Inc., such as theMetaFrame or Citrix Presentation Server™, and/or any of the Microsoft®Windows Terminal Services manufactured by the Microsoft Corporation. Inone embodiment, the application is an ICA client, developed by CitrixSystems, Inc. of Fort Lauderdale, Fla. In other embodiments, theapplication includes a Remote Desktop (RDP) client, developed byMicrosoft Corporation of Redmond, Wash. Also, the server 106 may run anapplication, which for example, may be an application server providingemail services such as Microsoft Exchange manufactured by the MicrosoftCorporation of Redmond, Wash., a web or Internet server, or a desktopsharing server, or a collaboration server. In some embodiments, any ofthe applications may comprise any type of hosted service or products,such as GoToMeeting™ provided by Citrix Online Division, Inc. of SantaBarbara, Calif., WebEx™ provided by WebEx, Inc. of Santa Clara, Calif.,or Microsoft Office Live Meeting provided by Microsoft Corporation ofRedmond, Wash.

Still referring to FIG. 1D, an embodiment of the network environment mayinclude a monitoring server 106A. The monitoring server 106A may includeany type and form performance monitoring service 198. The performancemonitoring service 198 may include monitoring, measurement and/ormanagement software and/or hardware, including data collection,aggregation, analysis, management and reporting. In one embodiment, theperformance monitoring service 198 includes one or more monitoringagents 197. The monitoring agent 197 includes any software, hardware orcombination thereof for performing monitoring, measurement and datacollection activities on a device, such as a client 102, server 106 oran appliance 200, 205. In some embodiments, the monitoring agent 197includes any type and form of script, such as Visual Basic script, orJavascript. In one embodiment, the monitoring agent 197 executestransparently to any application and/or user of the device. In someembodiments, the monitoring agent 197 is installed and operatedunobtrusively to the application or client. In yet another embodiment,the monitoring agent 197 is installed and operated without anyinstrumentation for the application or device.

In some embodiments, the monitoring agent 197 monitors, measures andcollects data on a predetermined frequency. In other embodiments, themonitoring agent 197 monitors, measures and collects data based upondetection of any type and form of event. For example, the monitoringagent 197 may collect data upon detection of a request for a web page orreceipt of an HTTP response. In another example, the monitoring agent197 may collect data upon detection of any user input events, such as amouse click. The monitoring agent 197 may report or provide anymonitored, measured or collected data to the monitoring service 198. Inone embodiment, the monitoring agent 197 transmits information to themonitoring service 198 according to a schedule or a predeterminedfrequency. In another embodiment, the monitoring agent 197 transmitsinformation to the monitoring service 198 upon detection of an event.

In some embodiments, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of any networkresource or network infrastructure element, such as a client, server,server farm, appliance 200, appliance 205, or network connection. In oneembodiment, the monitoring service 198 and/or monitoring agent 197performs monitoring and performance measurement of any transport layerconnection, such as a TCP or UDP connection. In another embodiment, themonitoring service 198 and/or monitoring agent 197 monitors and measuresnetwork latency. In yet one embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures bandwidth utilization.

In other embodiments, the monitoring service 198 and/or monitoring agent197 monitors and measures end-user response times. In some embodiments,the monitoring service 198 performs monitoring and performancemeasurement of an application. In another embodiment, the monitoringservice 198 and/or monitoring agent 197 performs monitoring andperformance measurement of any session or connection to the application.In one embodiment, the monitoring service 198 and/or monitoring agent197 monitors and measures performance of a browser. In anotherembodiment, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of HTTP based transactions. In someembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of a Voice over IP (VoIP) applicationor session. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors and measures performance of a remotedisplay protocol application, such as an ICA client or RDP client. Inyet another embodiment, the monitoring service 198 and/or monitoringagent 197 monitors and measures performance of any type and form ofstreaming media. In still a further embodiment, the monitoring service198 and/or monitoring agent 197 monitors and measures performance of ahosted application or a Software-As-A-Service (SaaS) delivery model.

In some embodiments, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of one or moretransactions, requests or responses related to application. In otherembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures any portion of an application layer stack, such asany .NET or J2EE calls. In one embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures database or SQLtransactions. In yet another embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures any method, functionor application programming interface (API) call.

In one embodiment, the monitoring service 198 and/or monitoring agent197 performs monitoring and performance measurement of a delivery ofapplication and/or data from a server to a client via one or moreappliances, such as appliance 200 and/or appliance 205. In someembodiments, the monitoring service 198 and/or monitoring agent 197monitors and measures performance of delivery of a virtualizedapplication. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors and measures performance of delivery of astreaming application. In another embodiment, the monitoring service 198and/or monitoring agent 197 monitors and measures performance ofdelivery of a desktop application to a client and/or the execution ofthe desktop application on the client. In another embodiment, themonitoring service 198 and/or monitoring agent 197 monitors and measuresperformance of a client/server application.

In one embodiment, the monitoring service 198 and/or monitoring agent197 is designed and constructed to provide application performancemanagement for the application delivery system 190. For example, themonitoring service 198 and/or monitoring agent 197 may monitor, measureand manage the performance of the delivery of applications via theCitrix Presentation Server. In this example, the monitoring service 198and/or monitoring agent 197 monitors individual ICA sessions. Themonitoring service 198 and/or monitoring agent 197 may measure the totaland per session system resource usage, as well as application andnetworking performance. The monitoring service 198 and/or monitoringagent 197 may identify the active servers for a given user and/or usersession. In some embodiments, the monitoring service 198 and/ormonitoring agent 197 monitors back-end connections between theapplication delivery system 190 and an application and/or databaseserver. The monitoring service 198 and/or monitoring agent 197 maymeasure network latency, delay and volume per user-session or ICAsession.

In some embodiments, the monitoring service 198 and/or monitoring agent197 measures and monitors memory usage for the application deliverysystem 190, such as total memory usage, per user session and/or perprocess. In other embodiments, the monitoring service 198 and/ormonitoring agent 197 measures and monitors CPU usage the applicationdelivery system 190, such as total CPU usage, per user session and/orper process. In another embodiments, the monitoring service 198 and/ormonitoring agent 197 measures and monitors the time required to log-into an application, a server, or the application delivery system, such asCitrix Presentation Server. In one embodiment, the monitoring service198 and/or monitoring agent 197 measures and monitors the duration auser is logged into an application, a server, or the applicationdelivery system 190. In some embodiments, the monitoring service 198and/or monitoring agent 197 measures and monitors active and inactivesession counts for an application, server or application delivery systemsession. In yet another embodiment, the monitoring service 198 and/ormonitoring agent 197 measures and monitors user session latency.

In yet further embodiments, the monitoring service 198 and/or monitoringagent 197 measures and monitors measures and monitors any type and formof server metrics. In one embodiment, the monitoring service 198 and/ormonitoring agent 197 measures and monitors metrics related to systemmemory, CPU usage, and disk storage. In another embodiment, themonitoring service 198 and/or monitoring agent 197 measures and monitorsmetrics related to page faults, such as page faults per second. In otherembodiments, the monitoring service 198 and/or monitoring agent 197measures and monitors round-trip time metrics. In yet anotherembodiment, the monitoring service 198 and/or monitoring agent 197measures and monitors metrics related to application crashes, errorsand/or hangs.

In some embodiments, the monitoring service 198 and monitoring agent 198includes any of the product embodiments referred to as EdgeSightmanufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. In anotherembodiment, the performance monitoring service 198 and/or monitoringagent 198 includes any portion of the product embodiments referred to asthe TrueView product suite manufactured by the Symphoniq Corporation ofPalo Alto, California. In one embodiment, the performance monitoringservice 198 and/or monitoring agent 198 includes any portion of theproduct embodiments referred to as the TeaLeaf CX product suitemanufactured by the TeaLeaf Technology Inc. of San Francisco, Calif. Inother embodiments, the performance monitoring service 198 and/ormonitoring agent 198 includes any portion of the business servicemanagement products, such as the BMC Performance Manager and Patrolproducts, manufactured by BMC Software, Inc. of Houston, Tex.

The client 102, server 106, and appliance 200 may be deployed as and/orexecuted on any type and form of computing device, such as a computer,network device or appliance capable of communicating on any type andform of network and performing the operations described herein. FIGS. 1Eand 1F depict block diagrams of a computing device 100 useful forpracticing an embodiment of the client 102, server 106 or appliance 200.As shown in FIGS. 1E and 1F, each computing device 100 includes acentral processing unit 101, and a main memory unit 122. As shown inFIG. 1E, a computing device 100 may include a visual display device 124,a keyboard 126 and/or a pointing device 127, such as a mouse. Eachcomputing device 100 may also include additional optional elements, suchas one or more input/output devices 130 a-130 b (generally referred tousing reference numeral 130), and a cache memory 140 in communicationwith the central processing unit 101.

The central processing unit 101 is any logic circuitry that responds toand processes instructions fetched from the main memory unit 122. Inmany embodiments, the central processing unit is provided by amicroprocessor unit, such as: those manufactured by Intel Corporation ofMountain View, Calif.; those manufactured by Motorola Corporation ofSchaumburg, Ill.; those manufactured by Transmeta Corporation of SantaClara, Calif.; the RS/6000 processor, those manufactured byInternational Business Machines of White Plains, N.Y.; or thosemanufactured by Advanced Micro Devices of Sunnyvale, Calif. Thecomputing device 100 may be based on any of these processors, or anyother processor capable of operating as described herein.

Main memory unit 122 may be one or more memory chips capable of storingdata and allowing any storage location to be directly accessed by themicroprocessor 101, such as Static random access memory (SRAM), BurstSRAM or SynchBurst SRAM (BSRAM), Dynamic random access memory (DRAM),Fast Page Mode DRAM (FPM DRAM), Enhanced DRAM (EDRAM), Extended DataOutput RAM (EDO RAM), Extended Data Output DRAM (EDO DRAM), BurstExtended Data Output DRAM (BEDO DRAM), Enhanced DRAM (EDRAM),synchronous DRAM (SDRAM), JEDEC SRAM, PC100 SDRAM, Double Data RateSDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), SyncLink DRAM (SLDRAM),Direct Rambus DRAM (DRDRAM), or Ferroelectric RAM (FRAM). The mainmemory 122 may be based on any of the above described memory chips, orany other available memory chips capable of operating as describedherein. In the embodiment shown in FIG. 1E, the processor 101communicates with main memory 122 via a system bus 150 (described inmore detail below). FIG. 1F depicts an embodiment of a computing device100 in which the processor communicates directly with main memory 122via a memory port 103. For example, in FIG. 1F the main memory 122 maybe DRDRAM.

FIG. 1F depicts an embodiment in which the main processor 101communicates directly with cache memory 140 via a secondary bus,sometimes referred to as a backside bus. In other embodiments, the mainprocessor 101 communicates with cache memory 140 using the system bus150. Cache memory 140 typically has a faster response time than mainmemory 122 and is typically provided by SRAM, BSRAM, or EDRAM. In theembodiment shown in FIG. 1F, the processor 101 communicates with variousI/O devices 130 via a local system bus 150. Various busses may be usedto connect the central processing unit 101 to any of the I/O devices130, including a VESA VL bus, an ISA bus, an EISA bus, a MicroChannelArchitecture (MCA) bus, a PCI bus, a PCI-X bus, a PCI-Express bus, or aNuBus. For embodiments in which the I/O device is a video display 124,the processor 101 may use an Advanced Graphics Port (AGP) to communicatewith the display 124. FIG. 1F depicts an embodiment of a computer 100 inwhich the main processor 101 communicates directly with I/O device 130 bvia HyperTransport, Rapid I/O, or InfiniBand. FIG. 1F also depicts anembodiment in which local busses and direct communication are mixed: theprocessor 101 communicates with I/O device 130 b using a localinterconnect bus while communicating with I/O device 130 a directly.

The computing device 100 may support any suitable installation device116, such as a floppy disk drive for receiving floppy disks such as3.5-inch, 5.25-inch disks or ZIP disks, a CD-ROM drive, a CD-R/RW drive,a DVD-ROM drive, tape drives of various formats, USB device, hard-driveor any other device suitable for installing software and programs suchas any client agent 120, or portion thereof. The computing device 100may further comprise a storage device 128, such as one or more hard diskdrives or redundant arrays of independent disks, for storing anoperating system and other related software, and for storing applicationsoftware programs such as any program related to the client agent 120.Optionally, any of the installation devices 116 could also be used asthe storage device 128. Additionally, the operating system and thesoftware can be run from a bootable medium, for example, a bootable CD,such as KNOPPIX®, a bootable CD for GNU/Linux that is available as aGNU/Linux distribution from knoppix.net.

Furthermore, the computing device 100 may include a network interface118 to interface to a Local Area Network (LAN), Wide Area Network (WAN)or the Internet through a variety of connections including, but notlimited to, standard telephone lines, LAN or WAN links (e.g., 802.11,T1, T3, 56 kb, X.25), broadband connections (e.g., ISDN, Frame Relay,ATM), wireless connections, or some combination of any or all of theabove. The network interface 118 may comprise a built-in networkadapter, network interface card, PCMCIA network card, card bus networkadapter, wireless network adapter, USB network adapter, modem or anyother device suitable for interfacing the computing device 100 to anytype of network capable of communication and performing the operationsdescribed herein. A wide variety of I/O devices 130 a-130 n may bepresent in the computing device 100. Input devices include keyboards,mice, trackpads, trackballs, microphones, and drawing tablets. Outputdevices include video displays, speakers, inkjet printers, laserprinters, and dye-sublimation printers. The I/O devices 130 may becontrolled by an I/O controller 123 as shown in FIG. 1E. The I/Ocontroller may control one or more I/O devices such as a keyboard 126and a pointing device 127, e.g., a mouse or optical pen. Furthermore, anI/O device may also provide storage 128 and/or an installation medium116 for the computing device 100. In still other embodiments, thecomputing device 100 may provide USB connections to receive handheld USBstorage devices such as the USB Flash Drive line of devices manufacturedby Twintech Industry, Inc. of Los Alamitos, California.

In some embodiments, the computing device 100 may comprise or beconnected to multiple display devices 124 a-124 n, which each may be ofthe same or different type and/or form. As such, any of the I/O devices130 a-130 n and/or the I/O controller 123 may comprise any type and/orform of suitable hardware, software, or combination of hardware andsoftware to support, enable or provide for the connection and use ofmultiple display devices 124 a-124 n by the computing device 100. Forexample, the computing device 100 may include any type and/or form ofvideo adapter, video card, driver, and/or library to interface,communicate, connect or otherwise use the display devices 124 a-124 n.In one embodiment, a video adapter may comprise multiple connectors tointerface to multiple display devices 124 a-124 n. In other embodiments,the computing device 100 may include multiple video adapters, with eachvideo adapter connected to one or more of the display devices 124 a-124n. In some embodiments, any portion of the operating system of thecomputing device 100 may be configured for using multiple displays 124a-124 n. In other embodiments, one or more of the display devices 124a-124 n may be provided by one or more other computing devices, such ascomputing devices 100 a and 100 b connected to the computing device 100,for example, via a network. These embodiments may include any type ofsoftware designed and constructed to use another computer's displaydevice as a second display device 124 a for the computing device 100.One ordinarily skilled in the art will recognize and appreciate thevarious ways and embodiments that a computing device 100 may beconfigured to have multiple display devices 124 a-124 n.

In further embodiments, an I/O device 130 may be a bridge 170 betweenthe system bus 150 and an external communication bus, such as a USB bus,an Apple Desktop Bus, an RS-232 serial connection, a SCSI bus, aFireWire bus, a FireWire 800 bus, an Ethernet bus, an AppleTalk bus, aGigabit Ethernet bus, an Asynchronous Transfer Mode bus, a HIPPI bus, aSuper HIPPI bus, a SerialPlus bus, a SCI/LAMP bus, a FibreChannel bus,or a Serial Attached small computer system interface bus.

A computing device 100 of the sort depicted in FIGS. 1E and 1F typicallyoperate under the control of operating systems, which control schedulingof tasks and access to system resources. The computing device 100 can berunning any operating system such as any of the versions of theMicrosoft® Windows operating systems, the different releases of the Unixand Linux operating systems, any version of the Mac OS® for Macintoshcomputers, any embedded operating system, any real-time operatingsystem, any open source operating system, any proprietary operatingsystem, any operating systems for mobile computing devices, or any otheroperating system capable of running on the computing device andperforming the operations described herein. Typical operating systemsinclude: WINDOWS 3.x, WINDOWS 95, WINDOWS 98, WINDOWS 2000, WINDOWS NT3.51, WINDOWS NT 4.0, WINDOWS CE, and WINDOWS XP, all of which aremanufactured by Microsoft Corporation of Redmond, Wash.; MacOS,manufactured by Apple Computer of Cupertino, California; OS/2,manufactured by International Business Machines of Armonk, N.Y.; andLinux, a freely-available operating system distributed by Caldera Corp.of Salt Lake City, Utah, or any type and/or form of a Unix operatingsystem, among others.

In other embodiments, the computing device 100 may have differentprocessors, operating systems, and input devices consistent with thedevice. For example, in one embodiment the computer 100 is a Treo 180,270, 1060, 600 or 650 smart phone manufactured by Palm, Inc. In thisembodiment, the Treo smart phone is operated under the control of thePalmOS operating system and includes a stylus input device as well as afive-way navigator device. Moreover, the computing device 100 can be anyworkstation, desktop computer, laptop or notebook computer, server,handheld computer, mobile telephone, any other computer, or other formof computing or telecommunications device that is capable ofcommunication and that has sufficient processor power and memorycapacity to perform the operations described herein.

As shown in FIG. 1G, the computing device 100 may comprise multipleprocessors and may provide functionality for simultaneous execution ofinstructions or for simultaneous execution of one instruction on morethan one piece of data. In some embodiments, the computing device 100may comprise a parallel processor with one or more cores. In one ofthese embodiments, the computing device 100 is a shared memory paralleldevice, with multiple processors and/or multiple processor cores,accessing all available memory as a single global address space. Inanother of these embodiments, the computing device 100 is a distributedmemory parallel device with multiple processors each accessing localmemory only. In still another of these embodiments, the computing device100 has both some memory which is shared and some memory which can onlybe accessed by particular processors or subsets of processors. In stilleven another of these embodiments, the computing device 100, such as amulti-core microprocessor, combines two or more independent processorsinto a single package, often a single integrated circuit (IC). In yetanother of these embodiments, the computing device 100 includes a chiphaving a CELL BROADBAND ENGINE architecture and including a Powerprocessor element and a plurality of synergistic processing elements,the Power processor element and the plurality of synergistic processingelements linked together by an internal high speed bus, which may bereferred to as an element interconnect bus.

In some embodiments, the processors provide functionality for executionof a single instruction simultaneously on multiple pieces of data(SIMD). In other embodiments, the processors provide functionality forexecution of multiple instructions simultaneously on multiple pieces ofdata (MIMD). In still other embodiments, the processor may use anycombination of SIMD and MIMD cores in a single device.

In some embodiments, the computing device 100 may comprise a graphicsprocessing unit. In one of these embodiments, depicted in FIG. 1H, thecomputing device 100 includes at least one central processing unit 101and at least one graphics processing unit. In another of theseembodiments, the computing device 100 includes at least one parallelprocessing unit and at least one graphics processing unit. In stillanother of these embodiments, the computing device 100 includes aplurality of processing units of any type, one of the plurality ofprocessing units comprising a graphics processing unit.

In some embodiments, a first computing device 100 a executes anapplication on behalf of a user of a client computing device 100 b. Inother embodiments, a computing device 100 a executes a virtual machine,which provides an execution session within which applications execute onbehalf of a user or a client computing devices 100 b. In one of theseembodiments, the execution session is a hosted desktop session. Inanother of these embodiments, the computing device 100 executes aterminal services session. The terminal services session may provide ahosted desktop environment. In still another of these embodiments, theexecution session provides access to a computing environment, which maycomprise one or more of: an application, a plurality of applications, adesktop application, and a desktop session in which one or moreapplications may execute.

B. Appliance Architecture

FIG. 2A illustrates an example embodiment of the appliance 200. Thearchitecture of the appliance 200 in FIG. 2A is provided by way ofillustration only and is not intended to be limiting. As shown in FIG.2, appliance 200 comprises a hardware layer 206 and a software layerdivided into a user space 202 and a kernel space 204.

Hardware layer 206 provides the hardware elements upon which programsand services within kernel space 204 and user space 202 are executed.Hardware layer 206 also provides the structures and elements which allowprograms and services within kernel space 204 and user space 202 tocommunicate data both internally and externally with respect toappliance 200. As shown in FIG. 2, the hardware layer 206 includes aprocessing unit 262 for executing software programs and services, amemory 264 for storing software and data, network ports 266 fortransmitting and receiving data over a network, and an encryptionprocessor 260 for performing functions related to Secure Sockets Layerprocessing of data transmitted and received over the network. In someembodiments, the central processing unit 262 may perform the functionsof the encryption processor 260 in a single processor. Additionally, thehardware layer 206 may comprise multiple processors for each of theprocessing unit 262 and the encryption processor 260. The processor 262may include any of the processors 101 described above in connection withFIGS. 1E and 1F. For example, in one embodiment, the appliance 200comprises a first processor 262 and a second processor 262′. In otherembodiments, the processor 262 or 262′ comprises a multi-core processor.

Although the hardware layer 206 of appliance 200 is generallyillustrated with an encryption processor 260, processor 260 may be aprocessor for performing functions related to any encryption protocol,such as the Secure Socket Layer (SSL) or Transport Layer Security (TLS)protocol. In some embodiments, the processor 260 may be a generalpurpose processor (GPP), and in further embodiments, may have executableinstructions for performing processing of any security related protocol.

Although the hardware layer 206 of appliance 200 is illustrated withcertain elements in FIG. 2, the hardware portions or components ofappliance 200 may comprise any type and form of elements, hardware orsoftware, of a computing device, such as the computing device 100illustrated and discussed herein in conjunction with FIGS. 1E and 1F. Insome embodiments, the appliance 200 may comprise a server, gateway,router, switch, bridge or other type of computing or network device, andhave any hardware and/or software elements associated therewith.

The operating system of appliance 200 allocates, manages, or otherwisesegregates the available system memory into kernel space 204 and userspace 204. In example software architecture 200, the operating systemmay be any type and/or form of Unix operating system although theinvention is not so limited. As such, the appliance 200 can be runningany operating system such as any of the versions of the Microsoft®Windows operating systems, the different releases of the Unix and Linuxoperating systems, any version of the Mac OS® for Macintosh computers,any embedded operating system, any network operating system, anyreal-time operating system, any open source operating system, anyproprietary operating system, any operating systems for mobile computingdevices or network devices, or any other operating system capable ofrunning on the appliance 200 and performing the operations describedherein.

The kernel space 204 is reserved for running the kernel 230, includingany device drivers, kernel extensions or other kernel related software.As known to those skilled in the art, the kernel 230 is the core of theoperating system, and provides access, control, and management ofresources and hardware-related elements of the application 104. Inaccordance with an embodiment of the appliance 200, the kernel space 204also includes a number of network services or processes working inconjunction with a cache manager 232, sometimes also referred to as theintegrated cache, the benefits of which are described in detail furtherherein. Additionally, the embodiment of the kernel 230 will depend onthe embodiment of the operating system installed, configured, orotherwise used by the device 200.

In one embodiment, the device 200 comprises one network stack 267, suchas a TCP/IP based stack, for communicating with the client 102 and/orthe server 106. In one embodiment, the network stack 267 is used tocommunicate with a first network, such as network 108, and a secondnetwork 110. In some embodiments, the device 200 terminates a firsttransport layer connection, such as a TCP connection of a client 102,and establishes a second transport layer connection to a server 106 foruse by the client 102, e.g., the second transport layer connection isterminated at the appliance 200 and the server 106. The first and secondtransport layer connections may be established via a single networkstack 267. In other embodiments, the device 200 may comprise multiplenetwork stacks, for example 267 and 267′, and the first transport layerconnection may be established or terminated at one network stack 267,and the second transport layer connection on the second network stack267′. For example, one network stack may be for receiving andtransmitting network packet on a first network, and another networkstack for receiving and transmitting network packets on a secondnetwork. In one embodiment, the network stack 267 comprises a buffer 243for queuing one or more network packets for transmission by theappliance 200.

As shown in FIG. 2, the kernel space 204 includes the cache manager 232,a high-speed layer 2-7 integrated packet engine 240, an encryptionengine 234, a policy engine 236 and multi-protocol compression logic238. Running these components or processes 232, 240, 234, 236 and 238 inkernel space 204 or kernel mode instead of the user space 202 improvesthe performance of each of these components, alone and in combination.Kernel operation means that these components or processes 232, 240, 234,236 and 238 run in the core address space of the operating system of thedevice 200. For example, running the encryption engine 234 in kernelmode improves encryption performance by moving encryption and decryptionoperations to the kernel, thereby reducing the number of transitionsbetween the memory space or a kernel thread in kernel mode and thememory space or a thread in user mode. For example, data obtained inkernel mode may not need to be passed or copied to a process or threadrunning in user mode, such as from a kernel level data structure to auser level data structure. In another aspect, the number of contextswitches between kernel mode and user mode are also reduced.Additionally, synchronization of and communications between any of thecomponents or processes 232, 240, 235, 236 and 238 can be performed moreefficiently in the kernel space 204.

In some embodiments, any portion of the components 232, 240, 234, 236and 238 may run or operate in the kernel space 204, while other portionsof these components 232, 240, 234, 236 and 238 may run or operate inuser space 202. In one embodiment, the appliance 200 uses a kernel-leveldata structure providing access to any portion of one or more networkpackets, for example, a network packet comprising a request from aclient 102 or a response from a server 106. In some embodiments, thekernel-level data structure may be obtained by the packet engine 240 viaa transport layer driver interface or filter to the network stack 267.The kernel-level data structure may comprise any interface and/or dataaccessible via the kernel space 204 related to the network stack 267,network traffic or packets received or transmitted by the network stack267. In other embodiments, the kernel-level data structure may be usedby any of the components or processes 232, 240, 234, 236 and 238 toperform the desired operation of the component or process. In oneembodiment, a component 232, 240, 234, 236 and 238 is running in kernelmode 204 when using the kernel-level data structure, while in anotherembodiment, the component 232, 240, 234, 236 and 238 is running in usermode when using the kernel-level data structure. In some embodiments,the kernel-level data structure may be copied or passed to a secondkernel-level data structure, or any desired user-level data structure.

The cache manager 232 may comprise software, hardware or any combinationof software and hardware to provide cache access, control and managementof any type and form of content, such as objects or dynamicallygenerated objects served by the originating servers 106. The data,objects or content processed and stored by the cache manager 232 maycomprise data in any format, such as a markup language, or communicatedvia any protocol. In some embodiments, the cache manager 232 duplicatesoriginal data stored elsewhere or data previously computed, generated ortransmitted, in which the original data may require longer access timeto fetch, compute or otherwise obtain relative to reading a cache memoryelement. Once the data is stored in the cache memory element, future usecan be made by accessing the cached copy rather than refetching orrecomputing the original data, thereby reducing the access time. In someembodiments, the cache memory element may comprise a data object inmemory 264 of device 200. In other embodiments, the cache memory elementmay comprise memory having a faster access time than memory 264. Inanother embodiment, the cache memory element may comprise any type andform of storage element of the device 200, such as a portion of a harddisk. In some embodiments, the processing unit 262 may provide cachememory for use by the cache manager 232. In yet further embodiments, thecache manager 232 may use any portion and combination of memory,storage, or the processing unit for caching data, objects, and othercontent.

Furthermore, the cache manager 232 includes any logic, functions, rules,or operations to perform any embodiments of the techniques of theappliance 200 described herein. For example, the cache manager 232includes logic or functionality to invalidate objects based on theexpiration of an invalidation time period or upon receipt of aninvalidation command from a client 102 or server 106. In someembodiments, the cache manager 232 may operate as a program, service,process or task executing in the kernel space 204, and in otherembodiments, in the user space 202. In one embodiment, a first portionof the cache manager 232 executes in the user space 202 while a secondportion executes in the kernel space 204. In some embodiments, the cachemanager 232 can comprise any type of general purpose processor (GPP), orany other type of integrated circuit, such as a Field Programmable GateArray (FPGA), Programmable Logic Device (PLD), or Application SpecificIntegrated Circuit (ASIC).

The policy engine 236 may include, for example, an intelligentstatistical engine or other programmable application(s). In oneembodiment, the policy engine 236 provides a configuration mechanism toallow a user to identify, specify, define or configure a caching policy.Policy engine 236, in some embodiments, also has access to memory tosupport data structures such as lookup tables or hash tables to enableuser-selected caching policy decisions. In other embodiments, the policyengine 236 may comprise any logic, rules, functions or operations todetermine and provide access, control and management of objects, data orcontent being cached by the appliance 200 in addition to access, controland management of security, network traffic, network access, compressionor any other function or operation performed by the appliance 200.Further examples of specific caching policies are further describedherein.

The encryption engine 234 comprises any logic, business rules, functionsor operations for handling the processing of any security relatedprotocol, such as SSL or TLS, or any function related thereto. Forexample, the encryption engine 234 encrypts and decrypts networkpackets, or any portion thereof, communicated via the appliance 200. Theencryption engine 234 may also setup or establish SSL or TLS connectionson behalf of the client 102 a-102 n, server 106 a-106 n, or appliance200. As such, the encryption engine 234 provides offloading andacceleration of SSL processing. In one embodiment, the encryption engine234 uses a tunneling protocol to provide a virtual private networkbetween a client 102 a-102 n and a server 106 a-106 n. In someembodiments, the encryption engine 234 is in communication with theEncryption processor 260. In other embodiments, the encryption engine234 comprises executable instructions running on the Encryptionprocessor 260.

The multi-protocol compression engine 238 comprises any logic, businessrules, function or operations for compressing one or more protocols of anetwork packet, such as any of the protocols used by the network stack267 of the device 200. In one embodiment, multi-protocol compressionengine 238 compresses bi-directionally between clients 102 a-102 n andservers 106 a-106 n any TCP/IP based protocol, including MessagingApplication Programming Interface (MAPI) (email), File Transfer Protocol(FTP), HyperText Transfer Protocol (HTTP), Common Internet File System(CIFS) protocol (file transfer), Independent Computing Architecture(ICA) protocol, Remote Desktop Protocol (RDP), Wireless ApplicationProtocol (WAP), Mobile IP protocol, and Voice Over IP (VoIP) protocol.In other embodiments, multi-protocol compression engine 238 providescompression of Hypertext Markup Language (HTML) based protocols and insome embodiments, provides compression of any markup languages, such asthe Extensible Markup Language (XML). In one embodiment, themulti-protocol compression engine 238 provides compression of anyhigh-performance protocol, such as any protocol designed for appliance200 to appliance 200 communications. In another embodiment, themulti-protocol compression engine 238 compresses any payload of or anycommunication using a modified transport control protocol, such asTransaction TCP (T/TCP), TCP with selection acknowledgements (TCP-SACK),TCP with large windows (TCP-LW), a congestion prediction protocol suchas the TCP-Vegas protocol, and a TCP spoofing protocol.

As such, the multi-protocol compression engine 238 acceleratesperformance for users accessing applications via desktop clients, e.g.,Microsoft Outlook and non-Web thin clients, such as any client launchedby popular enterprise applications like Oracle, SAP and Siebel, and evenmobile clients, such as the Pocket PC. In some embodiments, themulti-protocol compression engine 238 by executing in the kernel mode204 and integrating with packet processing engine 240 accessing thenetwork stack 267 is able to compress any of the protocols carried bythe TCP/IP protocol, such as any application layer protocol.

High speed layer 2-7 integrated packet engine 240, also generallyreferred to as a packet processing engine or packet engine, isresponsible for managing the kernel-level processing of packets receivedand transmitted by appliance 200 via network ports 266. The high speedlayer 2-7 integrated packet engine 240 may comprise a buffer for queuingone or more network packets during processing, such as for receipt of anetwork packet or transmission of a network packet. Additionally, thehigh speed layer 2-7 integrated packet engine 240 is in communicationwith one or more network stacks 267 to send and receive network packetsvia network ports 266. The high speed layer 2-7 integrated packet engine240 works in conjunction with encryption engine 234, cache manager 232,policy engine 236 and multi-protocol compression logic 238. Inparticular, encryption engine 234 is configured to perform SSLprocessing of packets, policy engine 236 is configured to performfunctions related to traffic management such as request-level contentswitching and request-level cache redirection, and multi-protocolcompression logic 238 is configured to perform functions related tocompression and decompression of data.

The high speed layer 2-7 integrated packet engine 240 includes a packetprocessing timer 242. In one embodiment, the packet processing timer 242provides one or more time intervals to trigger the processing ofincoming, i.e., received, or outgoing, i.e., transmitted, networkpackets. In some embodiments, the high speed layer 2-7 integrated packetengine 240 processes network packets responsive to the timer 242. Thepacket processing timer 242 provides any type and form of signal to thepacket engine 240 to notify, trigger, or communicate a time relatedevent, interval or occurrence. In many embodiments, the packetprocessing timer 242 operates in the order of milliseconds, such as forexample 100 ms, 50 ms or 25 ms. For example, in some embodiments, thepacket processing timer 242 provides time intervals or otherwise causesa network packet to be processed by the high speed layer 2-7 integratedpacket engine 240 at a 10 ms time interval, while in other embodiments,at a 5 ms time interval, and still yet in further embodiments, as shortas a 3, 2, or 1 ms time interval. The high speed layer 2-7 integratedpacket engine 240 may be interfaced, integrated or in communication withthe encryption engine 234, cache manager 232, policy engine 236 andmulti-protocol compression engine 238 during operation. As such, any ofthe logic, functions, or operations of the encryption engine 234, cachemanager 232, policy engine 236 and multi-protocol compression logic 238may be performed responsive to the packet processing timer 242 and/orthe packet engine 240. Therefore, any of the logic, functions, oroperations of the encryption engine 234, cache manager 232, policyengine 236 and multi-protocol compression logic 238 may be performed atthe granularity of time intervals provided via the packet processingtimer 242, for example, at a time interval of less than or equal to 10ms. For example, in one embodiment, the cache manager 232 may performinvalidation of any cached objects responsive to the high speed layer2-7 integrated packet engine 240 and/or the packet processing timer 242.In another embodiment, the expiry or invalidation time of a cachedobject can be set to the same order of granularity as the time intervalof the packet processing timer 242, such as at every 10 ms.

In contrast to kernel space 204, user space 202 is the memory area orportion of the operating system used by user mode applications orprograms otherwise running in user mode. A user mode application may notaccess kernel space 204 directly and uses service calls in order toaccess kernel services. As shown in FIG. 2, user space 202 of appliance200 includes a graphical user interface (GUI) 210, a command lineinterface (CLI) 212, shell services 214, health monitoring program 216,and daemon services 218. GUI 210 and CLI 212 provide a means by which asystem administrator or other user can interact with and control theoperation of appliance 200, such as via the operating system of theappliance 200. The GUI 210 or CLI 212 can comprise code running in userspace 202 or kernel space 204. The GUI 210 may be any type and form ofgraphical user interface and may be presented via text, graphical orotherwise, by any type of program or application, such as a browser. TheCLI 212 may be any type and form of command line or text-basedinterface, such as a command line provided by the operating system. Forexample, the CLI 212 may comprise a shell, which is a tool to enableusers to interact with the operating system. In some embodiments, theCLI 212 may be provided via a bash, csh, tcsh, or ksh type shell. Theshell services 214 comprises the programs, services, tasks, processes orexecutable instructions to support interaction with the appliance 200 oroperating system by a user via the GUI 210 and/or CLI 212.

Health monitoring program 216 is used to monitor, check, report andensure that network systems are functioning properly and that users arereceiving requested content over a network. Health monitoring program216 comprises one or more programs, services, tasks, processes orexecutable instructions to provide logic, rules, functions or operationsfor monitoring any activity of the appliance 200. In some embodiments,the health monitoring program 216 intercepts and inspects any networktraffic passed via the appliance 200. In other embodiments, the healthmonitoring program 216 interfaces by any suitable means and/ormechanisms with one or more of the following: the encryption engine 234,cache manager 232, policy engine 236, multi-protocol compression logic238, packet engine 240, daemon services 218, and shell services 214. Assuch, the health monitoring program 216 may call any applicationprogramming interface (API) to determine a state, status, or health ofany portion of the appliance 200. For example, the health monitoringprogram 216 may ping or send a status inquiry on a periodic basis tocheck if a program, process, service or task is active and currentlyrunning. In another example, the health monitoring program 216 may checkany status, error or history logs provided by any program, process,service or task to determine any condition, status or error with anyportion of the appliance 200.

Daemon services 218 are programs that run continuously or in thebackground and handle periodic service requests received by appliance200. In some embodiments, a daemon service may forward the requests toother programs or processes, such as another daemon service 218 asappropriate. As known to those skilled in the art, a daemon service 218may run unattended to perform continuous or periodic system widefunctions, such as network control, or to perform any desired task. Insome embodiments, one or more daemon services 218 run in the user space202, while in other embodiments, one or more daemon services 218 run inthe kernel space.

Referring now to FIG. 2B, another embodiment of the appliance 200 isdepicted. In brief overview, the appliance 200 provides one or more ofthe following services, functionality or operations: SSL VPNconnectivity 280, switching/load balancing 284, Domain Name Serviceresolution 286, acceleration 288 and an application firewall 290 forcommunications between one or more clients 102 and one or more servers106. Each of the servers 106 may provide one or more network relatedservices 270 a-270 n (referred to as services 270). For example, aserver 106 may provide an http service 270. The appliance 200 comprisesone or more virtual servers or virtual internet protocol servers,referred to as a vServer, VIP server, or just VIP 275 a-275 n (alsoreferred herein as vServer 275). The vServer 275 receives, intercepts orotherwise processes communications between a client 102 and a server 106in accordance with the configuration and operations of the appliance200.

The vServer 275 may comprise software, hardware or any combination ofsoftware and hardware. The vServer 275 may comprise any type and form ofprogram, service, task, process or executable instructions operating inuser mode 202, kernel mode 204 or any combination thereof in theappliance 200. The vServer 275 includes any logic, functions, rules, oroperations to perform any embodiments of the techniques describedherein, such as SSL VPN 280, switching/load balancing 284, Domain NameService resolution 286, acceleration 288 and an application firewall290. In some embodiments, the vServer 275 establishes a connection to aservice 270 of a server 106. The service 275 may comprise any program,application, process, task or set of executable instructions capable ofconnecting to and communicating to the appliance 200, client 102 orvServer 275. For example, the service 275 may comprise a web server,http server, ftp, email or database server. In some embodiments, theservice 270 is a daemon process or network driver for listening,receiving and/or sending communications for an application, such asemail, database or an enterprise application. In some embodiments, theservice 270 may communicate on a specific IP address, or IP address andport.

In some embodiments, the vServer 275 applies one or more policies of thepolicy engine 236 to network communications between the client 102 andserver 106. In one embodiment, the policies are associated with avServer 275. In another embodiment, the policies are based on a user, ora group of users. In yet another embodiment, a policy is global andapplies to one or more vServers 275 a-275 n, and any user or group ofusers communicating via the appliance 200. In some embodiments, thepolicies of the policy engine have conditions upon which the policy isapplied based on any content of the communication, such as internetprotocol address, port, protocol type, header or fields in a packet, orthe context of the communication, such as user, group of the user,vServer 275, transport layer connection, and/or identification orattributes of the client 102 or server 106.

In other embodiments, the appliance 200 communicates or interfaces withthe policy engine 236 to determine authentication and/or authorizationof a remote user or a remote client 102 to access the computingenvironment 15, application, and/or data file from a server 106. Inanother embodiment, the appliance 200 communicates or interfaces withthe policy engine 236 to determine authentication and/or authorizationof a remote user or a remote client 102 to have the application deliverysystem 190 deliver one or more of the computing environment 15,application, and/or data file. In yet another embodiment, the appliance200 establishes a VPN or SSL VPN connection based on the policy engine's236 authentication and/or authorization of a remote user or a remoteclient 102. In one embodiment, the appliance 200 controls the flow ofnetwork traffic and communication sessions based on policies of thepolicy engine 236. For example, the appliance 200 may control the accessto a computing environment 15, application or data file based on thepolicy engine 236.

In some embodiments, the vServer 275 establishes a transport layerconnection, such as a TCP or UDP connection with a client 102 via theclient agent 120. In one embodiment, the vServer 275 listens for andreceives communications from the client 102. In other embodiments, thevServer 275 establishes a transport layer connection, such as a TCP orUDP connection with a client server 106. In one embodiment, the vServer275 establishes the transport layer connection to an internet protocoladdress and port of a server 270 running on the server 106. In anotherembodiment, the vServer 275 associates a first transport layerconnection to a client 102 with a second transport layer connection tothe server 106. In some embodiments, a vServer 275 establishes a pool oftransport layer connections to a server 106 and multiplexes clientrequests via the pooled transport layer connections.

In some embodiments, the appliance 200 provides a SSL VPN connection 280between a client 102 and a server 106. For example, a client 102 on afirst network 102 requests to establish a connection to a server 106 ona second network 104′. In some embodiments, the second network 104′ isnot routable from the first network 104. In other embodiments, theclient 102 is on a public network 104 and the server 106 is on a privatenetwork 104′, such as a corporate network. In one embodiment, the clientagent 120 intercepts communications of the client 102 on the firstnetwork 104, encrypts the communications, and transmits thecommunications via a first transport layer connection to the appliance200. The appliance 200 associates the first transport layer connectionon the first network 104 to a second transport layer connection to theserver 106 on the second network 104. The appliance 200 receives theintercepted communication from the client agent 102, decrypts thecommunications, and transmits the communication to the server 106 on thesecond network 104 via the second transport layer connection. The secondtransport layer connection may be a pooled transport layer connection.As such, the appliance 200 provides an end-to-end secure transport layerconnection for the client 102 between the two networks 104, 104′.

In one embodiment, the appliance 200 hosts an intranet internet protocolor IntranetIP 282 address of the client 102 on the virtual privatenetwork 104. The client 102 has a local network identifier, such as aninternet protocol (IP) address and/or host name on the first network104. When connected to the second network 104′ via the appliance 200,the appliance 200 establishes, assigns or otherwise provides anIntranetIP address 282, which is a network identifier, such as IPaddress and/or host name, for the client 102 on the second network 104′.The appliance 200 listens for and receives on the second or privatenetwork 104′ for any communications directed towards the client 102using the client's established IntranetIP 282. In one embodiment, theappliance 200 acts as or on behalf of the client 102 on the secondprivate network 104. For example, in another embodiment, a vServer 275listens for and responds to communications to the IntranetIP 282 of theclient 102. In some embodiments, if a computing device 100 on the secondnetwork 104′ transmits a request, the appliance 200 processes therequest as if it were the client 102. For example, the appliance 200 mayrespond to a ping to the client's IntranetIP 282. In another example,the appliance may establish a connection, such as a TCP or UDPconnection, with computing device 100 on the second network 104requesting a connection with the client's IntranetIP 282.

In some embodiments, the appliance 200 provides one or more of thefollowing acceleration techniques 288 to communications between theclient 102 and server 106: 1) compression; 2) decompression; 3)Transmission Control Protocol pooling; 4) Transmission Control Protocolmultiplexing; 5) Transmission Control Protocol buffering; and 6)caching. In one embodiment, the appliance 200 relieves servers 106 ofmuch of the processing load caused by repeatedly opening and closingtransport layers connections to clients 102 by opening one or moretransport layer connections with each server 106 and maintaining theseconnections to allow repeated data accesses by clients via the Internet.This technique is referred to herein as “connection pooling”.

In some embodiments, in order to seamlessly splice communications from aclient 102 to a server 106 via a pooled transport layer connection, theappliance 200 translates or multiplexes communications by modifyingsequence number and acknowledgment numbers at the transport layerprotocol level. This is referred to as “connection multiplexing”. Insome embodiments, no application layer protocol interaction is required.For example, in the case of an in-bound packet (that is, a packetreceived from a client 102), the source network address of the packet ischanged to that of an output port of appliance 200, and the destinationnetwork address is changed to that of the intended server. In the caseof an outbound packet (that is, one received from a server 106), thesource network address is changed from that of the server 106 to that ofan output port of appliance 200 and the destination address is changedfrom that of appliance 200 to that of the requesting client 102. Thesequence numbers and acknowledgment numbers of the packet are alsotranslated to sequence numbers and acknowledgement numbers expected bythe client 102 on the appliance's 200 transport layer connection to theclient 102. In some embodiments, the packet checksum of the transportlayer protocol is recalculated to account for these translations.

In another embodiment, the appliance 200 provides switching orload-balancing functionality 284 for communications between the client102 and server 106. In some embodiments, the appliance 200 distributestraffic and directs client requests to a server 106 based on layer 4 orapplication-layer request data. In one embodiment, although the networklayer or layer 2 of the network packet identifies a destination server106, the appliance 200 determines the server 106 to distribute thenetwork packet by application information and data carried as payload ofthe transport layer packet. In one embodiment, the health monitoringprograms 216 of the appliance 200 monitor the health of servers todetermine the server 106 for which to distribute a client's request. Insome embodiments, if the appliance 200 detects a server 106 is notavailable or has a load over a predetermined threshold, the appliance200 can direct or distribute client requests to another server 106.

In some embodiments, the appliance 200 acts as a Domain Name Service(DNS) resolver or otherwise provides resolution of a DNS request fromclients 102. In some embodiments, the appliance intercepts a DNS requesttransmitted by the client 102. In one embodiment, the appliance 200responds to a client's DNS request with an IP address of or hosted bythe appliance 200. In this embodiment, the client 102 transmits networkcommunication for the domain name to the appliance 200. In anotherembodiment, the appliance 200 responds to a client's DNS request with anIP address of or hosted by a second appliance 200′. In some embodiments,the appliance 200 responds to a client's DNS request with an IP addressof a server 106 determined by the appliance 200.

In yet another embodiment, the appliance 200 provides applicationfirewall functionality 290 for communications between the client 102 andserver 106. In one embodiment, the policy engine 236 provides rules fordetecting and blocking illegitimate requests. In some embodiments, theapplication firewall 290 protects against denial of service (DoS)attacks. In other embodiments, the appliance inspects the content ofintercepted requests to identify and block application-based attacks. Insome embodiments, the rules/policy engine 236 comprises one or moreapplication firewall or security control policies for providingprotections against various classes and types of web or Internet basedvulnerabilities, such as one or more of the following: 1) bufferoverflow, 2) CGI-BIN parameter manipulation, 3) form/hidden fieldmanipulation, 4) forceful browsing, 5) cookie or session poisoning, 6)broken access control list (ACLs) or weak passwords, 7) cross-sitescripting (XSS), 8) command injection, 9) SQL injection, 10) errortriggering sensitive information leak, 11) insecure use of cryptography,12) server misconfiguration, 13) back doors and debug options, 14)website defacement, 15) platform or operating systems vulnerabilities,and 16) zero-day exploits. In an embodiment, the application firewall290 provides HTML form field protection in the form of inspecting oranalyzing the network communication for one or more of the following: 1)required fields are returned, 2) no added field allowed, 3) read-onlyand hidden field enforcement, 4) drop-down list and radio button fieldconformance, and 5) form-field max-length enforcement. In someembodiments, the application firewall 290 ensures cookies are notmodified. In other embodiments, the application firewall 290 protectsagainst forceful browsing by enforcing legal URLs.

In still yet other embodiments, the application firewall 290 protectsany confidential information contained in the network communication. Theapplication firewall 290 may inspect or analyze any networkcommunication in accordance with the rules or polices of the engine 236to identify any confidential information in any field of the networkpacket. In some embodiments, the application firewall 290 identifies inthe network communication one or more occurrences of a credit cardnumber, password, social security number, name, patient code, contactinformation, and age. The encoded portion of the network communicationmay comprise these occurrences or the confidential information. Based onthese occurrences, in one embodiment, the application firewall 290 maytake a policy action on the network communication, such as preventtransmission of the network communication. In another embodiment, theapplication firewall 290 may rewrite, remove or otherwise mask suchidentified occurrence or confidential information.

Still referring to FIG. 2B, the appliance 200 may include a performancemonitoring agent 197 as discussed above in conjunction with FIG. 1D. Inone embodiment, the appliance 200 receives the monitoring agent 197 fromthe monitoring service 198 or monitoring server 106 as depicted in FIG.1D. In some embodiments, the appliance 200 stores the monitoring agent197 in storage, such as disk, for delivery to any client or server incommunication with the appliance 200. For example, in one embodiment,the appliance 200 transmits the monitoring agent 197 to a client uponreceiving a request to establish a transport layer connection. In otherembodiments, the appliance 200 transmits the monitoring agent 197 uponestablishing the transport layer connection with the client 102. Inanother embodiment, the appliance 200 transmits the monitoring agent 197to the client upon intercepting or detecting a request for a web page.In yet another embodiment, the appliance 200 transmits the monitoringagent 197 to a client or a server in response to a request from themonitoring server 198. In one embodiment, the appliance 200 transmitsthe monitoring agent 197 to a second appliance 200′ or appliance 205.

In other embodiments, the appliance 200 executes the monitoring agent197. In one embodiment, the monitoring agent 197 measures and monitorsthe performance of any application, program, process, service, task orthread executing on the appliance 200. For example, the monitoring agent197 may monitor and measure performance and operation of vServers275A-275N. In another embodiment, the monitoring agent 197 measures andmonitors the performance of any transport layer connections of theappliance 200. In some embodiments, the monitoring agent 197 measuresand monitors the performance of any user sessions traversing theappliance 200. In one embodiment, the monitoring agent 197 measures andmonitors the performance of any virtual private network connectionsand/or sessions traversing the appliance 200, such an SSL VPN session.In still further embodiments, the monitoring agent 197 measures andmonitors the memory, CPU and disk usage and performance of the appliance200. In yet another embodiment, the monitoring agent 197 measures andmonitors the performance of any acceleration technique 288 performed bythe appliance 200, such as SSL offloading, connection pooling andmultiplexing, caching, and compression. In some embodiments, themonitoring agent 197 measures and monitors the performance of any loadbalancing and/or content switching 284 performed by the appliance 200.In other embodiments, the monitoring agent 197 measures and monitors theperformance of application firewall 290 protection and processingperformed by the appliance 200.

C. Client Agent

Referring now to FIG. 3, an embodiment of the client agent 120 isdepicted. The client 102 includes a client agent 120 for establishingand exchanging communications with the appliance 200 and/or server 106via a network 104. In brief overview, the client 102 operates oncomputing device 100 having an operating system with a kernel mode 302and a user mode 303, and a network stack 310 with one or more layers 310a-310 b. The client 102 may have installed and/or execute one or moreapplications. In some embodiments, one or more applications maycommunicate via the network stack 310 to a network 104. One of theapplications, such as a web browser, may also include a first program322. For example, the first program 322 may be used in some embodimentsto install and/or execute the client agent 120, or any portion thereof.The client agent 120 includes an interception mechanism, or interceptor350, for intercepting network communications from the network stack 310from the one or more applications.

The network stack 310 of the client 102 may comprise any type and formof software, or hardware, or any combinations thereof, for providingconnectivity to and communications with a network. In one embodiment,the network stack 310 comprises a software implementation for a networkprotocol suite. The network stack 310 may comprise one or more networklayers, such as any networks layers of the Open Systems Interconnection(OSI) communications model as those skilled in the art recognize andappreciate. As such, the network stack 310 may comprise any type andform of protocols for any of the following layers of the OSI model: 1)physical link layer, 2) data link layer, 3) network layer, 4) transportlayer, 5) session layer, 6) presentation layer, and 7) applicationlayer. In one embodiment, the network stack 310 may comprise a transportcontrol protocol (TCP) over the network layer protocol of the internetprotocol (IP), generally referred to as TCP/IP. In some embodiments, theTCP/IP protocol may be carried over the Ethernet protocol, which maycomprise any of the family of IEEE wide-area-network (WAN) orlocal-area-network (LAN) protocols, such as those protocols covered bythe IEEE 802.3. In some embodiments, the network stack 310 comprises anytype and form of a wireless protocol, such as IEEE 802.11 and/or mobileinternet protocol.

In view of a TCP/IP based network, any TCP/IP based protocol may beused, including Messaging Application Programming Interface (MAPI)(email), File Transfer Protocol (FTP), HyperText Transfer Protocol(HTTP), Common Internet File System (CIFS) protocol (file transfer),Independent Computing Architecture (ICA) protocol, Remote DesktopProtocol (RDP), Wireless Application Protocol (WAP), Mobile IP protocol,and Voice Over IP (VoIP) protocol. In another embodiment, the networkstack 310 comprises any type and form of transport control protocol,such as a modified transport control protocol, for example a TransactionTCP (T/TCP), TCP with selection acknowledgements (TCP-SACK), TCP withlarge windows (TCP-LW), a congestion prediction protocol such as theTCP-Vegas protocol, and a TCP spoofing protocol. In other embodiments,any type and form of user datagram protocol (UDP), such as UDP over IP,may be used by the network stack 310, such as for voice communicationsor real-time data communications.

Furthermore, the network stack 310 may include one or more networkdrivers supporting the one or more layers, such as a TCP driver or anetwork layer driver. The network drivers may be included as part of theoperating system of the computing device 100 or as part of any networkinterface cards or other network access components of the computingdevice 100. In some embodiments, any of the network drivers of thenetwork stack 310 may be customized, modified or adapted to provide acustom or modified portion of the network stack 310 in support of any ofthe techniques described herein. In other embodiments, the accelerationprogram 302 is designed and constructed to operate with or work inconjunction with the network stack 310 installed or otherwise providedby the operating system of the client 102.

The network stack 310 comprises any type and form of interfaces forreceiving, obtaining, providing or otherwise accessing any informationand data related to network communications of the client 102. In oneembodiment, an interface to the network stack 310 comprises anapplication programming interface (API). The interface may also compriseany function call, hooking or filtering mechanism, event or call backmechanism, or any type of interfacing technique. The network stack 310via the interface may receive or provide any type and form of datastructure, such as an object, related to functionality or operation ofthe network stack 310. For example, the data structure may compriseinformation and data related to a network packet or one or more networkpackets. In some embodiments, the data structure comprises a portion ofthe network packet processed at a protocol layer of the network stack310, such as a network packet of the transport layer. In someembodiments, the data structure 325 comprises a kernel-level datastructure, while in other embodiments, the data structure 325 comprisesa user-mode data structure. A kernel-level data structure may comprise adata structure obtained or related to a portion of the network stack 310operating in kernel-mode 302, or a network driver or other softwarerunning in kernel-mode 302, or any data structure obtained or receivedby a service, process, task, thread or other executable instructionsrunning or operating in kernel-mode of the operating system.

Additionally, some portions of the network stack 310 may execute oroperate in kernel-mode 302, for example, the data link or network layer,while other portions execute or operate in user-mode 303, such as anapplication layer of the network stack 310. For example, a first portion310 a of the network stack may provide user-mode access to the networkstack 310 to an application while a second portion 310 a of the networkstack 310 provides access to a network. In some embodiments, a firstportion 310 a of the network stack may comprise one or more upper layersof the network stack 310, such as any of layers 5-7. In otherembodiments, a second portion 310 b of the network stack 310 comprisesone or more lower layers, such as any of layers 1-4. Each of the firstportion 310 a and second portion 310 b of the network stack 310 maycomprise any portion of the network stack 310, at any one or morenetwork layers, in user-mode 203, kernel-mode, 202, or combinationsthereof, or at any portion of a network layer or interface point to anetwork layer or any portion of or interface point to the user-mode 203and kernel-mode 203.

The interceptor 350 may comprise software, hardware, or any combinationof software and hardware. In one embodiment, the interceptor 350intercept a network communication at any point in the network stack 310,and redirects or transmits the network communication to a destinationdesired, managed or controlled by the interceptor 350 or client agent120. For example, the interceptor 350 may intercept a networkcommunication of a network stack 310 of a first network and transmit thenetwork communication to the appliance 200 for transmission on a secondnetwork 104. In some embodiments, the interceptor 350 comprises any typeinterceptor 350 comprises a driver, such as a network driver constructedand designed to interface and work with the network stack 310. In someembodiments, the client agent 120 and/or interceptor 350 operates at oneor more layers of the network stack 310, such as at the transport layer.In one embodiment, the interceptor 350 comprises a filter driver,hooking mechanism, or any form and type of suitable network driverinterface that interfaces to the transport layer of the network stack,such as via the transport driver interface (TDI). In some embodiments,the interceptor 350 interfaces to a first protocol layer, such as thetransport layer and another protocol layer, such as any layer above thetransport protocol layer, for example, an application protocol layer. Inone embodiment, the interceptor 350 may comprise a driver complying withthe Network Driver Interface Specification (NDIS), or a NDIS driver. Inanother embodiment, the interceptor 350 may comprise a mini-filter or amini-port driver. In one embodiment, the interceptor 350, or portionthereof, operates in kernel-mode 202. In another embodiment, theinterceptor 350, or portion thereof, operates in user-mode 203. In someembodiments, a portion of the interceptor 350 operates in kernel-mode202 while another portion of the interceptor 350 operates in user-mode203. In other embodiments, the client agent 120 operates in user-mode203 but interfaces via the interceptor 350 to a kernel-mode driver,process, service, task or portion of the operating system, such as toobtain a kernel-level data structure 225. In further embodiments, theinterceptor 350 is a user-mode application or program, such asapplication.

In one embodiment, the interceptor 350 intercepts any transport layerconnection requests. In these embodiments, the interceptor 350 executetransport layer application programming interface (API) calls to set thedestination information, such as destination IP address and/or port to adesired location for the location. In this manner, the interceptor 350intercepts and redirects the transport layer connection to a IP addressand port controlled or managed by the interceptor 350 or client agent120. In one embodiment, the interceptor 350 sets the destinationinformation for the connection to a local IP address and port of theclient 102 on which the client agent 120 is listening. For example, theclient agent 120 may comprise a proxy service listening on a local IPaddress and port for redirected transport layer communications. In someembodiments, the client agent 120 then communicates the redirectedtransport layer communication to the appliance 200.

In some embodiments, the interceptor 350 intercepts a Domain NameService (DNS) request. In one embodiment, the client agent 120 and/orinterceptor 350 resolves the DNS request. In another embodiment, theinterceptor transmits the intercepted DNS request to the appliance 200for DNS resolution. In one embodiment, the appliance 200 resolves theDNS request and communicates the DNS response to the client agent 120.In some embodiments, the appliance 200 resolves the DNS request viaanother appliance 200′ or a DNS server 106.

In yet another embodiment, the client agent 120 may comprise two agents120 and 120′. In one embodiment, a first agent 120 may comprise aninterceptor 350 operating at the network layer of the network stack 310.In some embodiments, the first agent 120 intercepts network layerrequests such as Internet Control Message Protocol (ICMP) requests(e.g., ping and traceroute). In other embodiments, the second agent 120′may operate at the transport layer and intercept transport layercommunications. In some embodiments, the first agent 120 interceptscommunications at one layer of the network stack 210 and interfaces withor communicates the intercepted communication to the second agent 120′.

The client agent 120 and/or interceptor 350 may operate at or interfacewith a protocol layer in a manner transparent to any other protocollayer of the network stack 310. For example, in one embodiment, theinterceptor 350 operates or interfaces with the transport layer of thenetwork stack 310 transparently to any protocol layer below thetransport layer, such as the network layer, and any protocol layer abovethe transport layer, such as the session, presentation or applicationlayer protocols. This allows the other protocol layers of the networkstack 310 to operate as desired and without modification for using theinterceptor 350. As such, the client agent 120 and/or interceptor 350can interface with the transport layer to secure, optimize, accelerate,route or load-balance any communications provided via any protocolcarried by the transport layer, such as any application layer protocolover TCP/IP.

Furthermore, the client agent 120 and/or interceptor may operate at orinterface with the network stack 310 in a manner transparent to anyapplication, a user of the client 102, and any other computing device,such as a server, in communications with the client 102. The clientagent 120 and/or interceptor 350 may be installed and/or executed on theclient 102 in a manner without modification of an application. In someembodiments, the user of the client 102 or a computing device incommunications with the client 102 are not aware of the existence,execution or operation of the client agent 120 and/or interceptor 350.As such, in some embodiments, the client agent 120 and/or interceptor350 is installed, executed, and/or operated transparently to anapplication, user of the client 102, another computing device, such as aserver, or any of the protocol layers above and/or below the protocollayer interfaced to by the interceptor 350.

The client agent 120 includes an acceleration program 302, a streamingclient 306, a collection agent 304, and/or monitoring agent 197. In oneembodiment, the client agent 120 comprises an Independent ComputingArchitecture (ICA) client, or any portion thereof, developed by CitrixSystems, Inc. of Fort Lauderdale, Fla., and is also referred to as anICA client. In some embodiments, the client 120 comprises an applicationstreaming client 306 for streaming an application from a server 106 to aclient 102. In some embodiments, the client agent 120 comprises anacceleration program 302 for accelerating communications between client102 and server 106. In another embodiment, the client agent 120 includesa collection agent 304 for performing end-point detection/scanning andcollecting end-point information for the appliance 200 and/or server106.

In some embodiments, the acceleration program 302 comprises aclient-side acceleration program for performing one or more accelerationtechniques to accelerate, enhance or otherwise improve a client'scommunications with and/or access to a server 106, such as accessing anapplication provided by a server 106. The logic, functions, and/oroperations of the executable instructions of the acceleration program302 may perform one or more of the following acceleration techniques: 1)multi-protocol compression, 2) transport control protocol pooling, 3)transport control protocol multiplexing, 4) transport control protocolbuffering, and 5) caching via a cache manager. Additionally, theacceleration program 302 may perform encryption and/or decryption of anycommunications received and/or transmitted by the client 102. In someembodiments, the acceleration program 302 performs one or more of theacceleration techniques in an integrated manner or fashion.Additionally, the acceleration program 302 can perform compression onany of the protocols, or multiple-protocols, carried as a payload of anetwork packet of the transport layer protocol.

The streaming client 306 comprises an application, program, process,service, task or executable instructions for receiving and executing astreamed application from a server 106. A server 106 may stream one ormore application data files to the streaming client 306 for playing,executing or otherwise causing to be executed the application on theclient 102. In some embodiments, the server 106 transmits a set ofcompressed or packaged application data files to the streaming client306. In some embodiments, the plurality of application files arecompressed and stored on a file server within an archive file such as aCAB, ZIP, SIT, TAR, JAR or other archive. In one embodiment, the server106 decompresses, unpackages or unarchives the application files andtransmits the files to the client 102. In another embodiment, the client102 decompresses, unpackages or unarchives the application files. Thestreaming client 306 dynamically installs the application, or portionthereof, and executes the application. In one embodiment, the streamingclient 306 may be an executable program. In some embodiments, thestreaming client 306 may be able to launch another executable program.

The collection agent 304 comprises an application, program, process,service, task or executable instructions for identifying, obtainingand/or collecting information about the client 102. In some embodiments,the appliance 200 transmits the collection agent 304 to the client 102or client agent 120. The collection agent 304 may be configuredaccording to one or more policies of the policy engine 236 of theappliance. In other embodiments, the collection agent 304 transmitscollected information on the client 102 to the appliance 200. In oneembodiment, the policy engine 236 of the appliance 200 uses thecollected information to determine and provide access, authenticationand authorization control of the client's connection to a network 104.

In one embodiment, the collection agent 304 comprises an end-pointdetection and scanning mechanism, which identifies and determines one ormore attributes or characteristics of the client. For example, thecollection agent 304 may identify and determine any one or more of thefollowing client-side attributes: 1) the operating system an/or aversion of an operating system, 2) a service pack of the operatingsystem, 3) a running service, 4) a running process, and 5) a file. Thecollection agent 304 may also identify and determine the presence orversions of any one or more of the following on the client: 1) antivirussoftware, 2) personal firewall software, 3) anti-spam software, and 4)internet security software. The policy engine 236 may have one or morepolicies based on any one or more of the attributes or characteristicsof the client or client-side attributes.

In some embodiments, the client agent 120 includes a monitoring agent197 as discussed in conjunction with FIGS. 1D and 2B. The monitoringagent 197 may be any type and form of script, such as Visual Basic orJava script. In one embodiment, the monitoring agent 197 monitors andmeasures performance of any portion of the client agent 120. Forexample, in some embodiments, the monitoring agent 197 monitors andmeasures performance of the acceleration program 302. In anotherembodiment, the monitoring agent 197 monitors and measures performanceof the streaming client 306. In other embodiments, the monitoring agent197 monitors and measures performance of the collection agent 304. Instill another embodiment, the monitoring agent 197 monitors and measuresperformance of the interceptor 350. In some embodiments, the monitoringagent 197 monitors and measures any resource of the client 102, such asmemory, CPU and disk.

The monitoring agent 197 may monitor and measure performance of anyapplication of the client. In one embodiment, the monitoring agent 197monitors and measures performance of a browser on the client 102. Insome embodiments, the monitoring agent 197 monitors and measuresperformance of any application delivered via the client agent 120. Inother embodiments, the monitoring agent 197 measures and monitors enduser response times for an application, such as web-based or HTTPresponse times. The monitoring agent 197 may monitor and measureperformance of an ICA or RDP client. In another embodiment, themonitoring agent 197 measures and monitors metrics for a user session orapplication session. In some embodiments, monitoring agent 197 measuresand monitors an ICA or RDP session. In one embodiment, the monitoringagent 197 measures and monitors the performance of the appliance 200 inaccelerating delivery of an application and/or data to the client 102.

In some embodiments and still referring to FIG. 3, a first program 322may be used to install and/or execute the client agent 120, or portionthereof, such as the interceptor 350, automatically, silently,transparently, or otherwise. In one embodiment, the first program 322comprises a plugin component, such an ActiveX control or Java control orscript that is loaded into and executed by an application. For example,the first program comprises an ActiveX control loaded and run by a webbrowser application, such as in the memory space or context of theapplication. In another embodiment, the first program 322 comprises aset of executable instructions loaded into and run by the application,such as a browser. In one embodiment, the first program 322 comprises adesigned and constructed program to install the client agent 120. Insome embodiments, the first program 322 obtains, downloads, or receivesthe client agent 120 via the network from another computing device. Inanother embodiment, the first program 322 is an installer program or aplug and play manager for installing programs, such as network drivers,on the operating system of the client 102.

D. Systems and Methods for Providing Virtualized Application DeliveryController

Referring now to FIG. 4A, a block diagram depicts one embodiment of avirtualization environment 400. In brief overview, a computing device100 includes a hypervisor layer, a virtualization layer, and a hardwarelayer. The hypervisor layer includes a hypervisor 401 (also referred toas a virtualization manager) that allocates and manages access to anumber of physical resources in the hardware layer (e.g., theprocessor(s) 421, and disk(s) 428) by at least one virtual machineexecuting in the virtualization layer. The virtualization layer includesat least one operating system 410 and a plurality of virtual resourcesallocated to the at least one operating system 410. Virtual resourcesmay include, without limitation, a plurality of virtual processors 432a, 432 b, 432 c (generally 432), and virtual disks 442 a, 442 b, 442 c(generally 442), as well as virtual resources such as virtual memory andvirtual network interfaces. The plurality of virtual resources and theoperating system 410 may be referred to as a virtual machine 406. Avirtual machine 406 may include a control operating system 405 incommunication with the hypervisor 401 and used to execute applicationsfor managing and configuring other virtual machines on the computingdevice 100.

In greater detail, a hypervisor 401 may provide virtual resources to anoperating system in any manner which simulates the operating systemhaving access to a physical device. A hypervisor 401 may provide virtualresources to any number of guest operating systems 410 a, 410 b(generally 410). In some embodiments, a computing device 100 executesone or more types of hypervisors. In these embodiments, hypervisors maybe used to emulate virtual hardware, partition physical hardware,virtualize physical hardware, and execute virtual machines that provideaccess to computing environments. Hypervisors may include thosemanufactured by VMWare, Inc., of Palo Alto, Calif.; the XEN hypervisor,an open source product whose development is overseen by the open sourceXen.org community; HyperV, VirtualServer or virtual PC hypervisorsprovided by Microsoft, or others. In some embodiments, a computingdevice 100 executing a hypervisor that creates a virtual machineplatform on which guest operating systems may execute is referred to asa host server. In one of these embodiments, for example, the computingdevice 100 is a XEN SERVER provided by Citrix Systems, Inc., of FortLauderdale, Fla.

In some embodiments, a hypervisor 401 executes within an operatingsystem executing on a computing device. In one of these embodiments, acomputing device executing an operating system and a hypervisor 401 maybe said to have a host operating system (the operating system executingon the computing device), and a guest operating system (an operatingsystem executing within a computing resource partition provided by thehypervisor 401). In other embodiments, a hypervisor 401 interactsdirectly with hardware on a computing device, instead of executing on ahost operating system. In one of these embodiments, the hypervisor 401may be said to be executing on “bare metal,” referring to the hardwarecomprising the computing device.

In some embodiments, a hypervisor 401 may create a virtual machine 406a-c (generally 406) in which an operating system 410 executes. In one ofthese embodiments, for example, the hypervisor 401 loads a virtualmachine image to create a virtual machine 406. In another of theseembodiments, the hypervisor 401 executes an operating system 410 withinthe virtual machine 406. In still another of these embodiments, thevirtual machine 406 executes an operating system 410.

In some embodiments, the hypervisor 401 controls processor schedulingand memory partitioning for a virtual machine 406 executing on thecomputing device 100. In one of these embodiments, the hypervisor 401controls the execution of at least one virtual machine 406. In anotherof these embodiments, the hypervisor 401 presents at least one virtualmachine 406 with an abstraction of at least one hardware resourceprovided by the computing device 100. In other embodiments, thehypervisor 401 controls whether and how physical processor capabilitiesare presented to the virtual machine 406.

A control operating system 405 may execute at least one application formanaging and configuring the guest operating systems. In one embodiment,the control operating system 405 may execute an administrativeapplication, such as an application including a user interface providingadministrators with access to functionality for managing the executionof a virtual machine, including functionality for executing a virtualmachine, terminating an execution of a virtual machine, or identifying atype of physical resource for allocation to the virtual machine. Inanother embodiment, the hypervisor 401 executes the control operatingsystem 405 within a virtual machine 406 created by the hypervisor 401.In still another embodiment, the control operating system 405 executesin a virtual machine 406 that is authorized to directly access physicalresources on the computing device 100. In some embodiments, a controloperating system 405 a on a computing device 100 a may exchange datawith a control operating system 405 b on a computing device 100 b, viacommunications between a hypervisor 401 a and a hypervisor 401 b. Inthis way, one or more computing devices 100 may exchange data with oneor more of the other computing devices 100 regarding processors andother physical resources available in a pool of resources. In one ofthese embodiments, this functionality allows a hypervisor to manage apool of resources distributed across a plurality of physical computingdevices. In another of these embodiments, multiple hypervisors manageone or more of the guest operating systems executed on one of thecomputing devices 100.

In one embodiment, the control operating system 405 executes in avirtual machine 406 that is authorized to interact with at least oneguest operating system 410. In another embodiment, a guest operatingsystem 410 communicates with the control operating system 405 via thehypervisor 401 in order to request access to a disk or a network. Instill another embodiment, the guest operating system 410 and the controloperating system 405 may communicate via a communication channelestablished by the hypervisor 401, such as, for example, via a pluralityof shared memory pages made available by the hypervisor 401.

In some embodiments, the control operating system 405 includes a networkback-end driver for communicating directly with networking hardwareprovided by the computing device 100. In one of these embodiments, thenetwork back-end driver processes at least one virtual machine requestfrom at least one guest operating system 110. In other embodiments, thecontrol operating system 405 includes a block back-end driver forcommunicating with a storage element on the computing device 100. In oneof these embodiments, the block back-end driver reads and writes datafrom the storage element based upon at least one request received from aguest operating system 410.

In one embodiment, the control operating system 405 includes a toolsstack 404. In another embodiment, a tools stack 404 providesfunctionality for interacting with the hypervisor 401, communicatingwith other control operating systems 405 (for example, on a secondcomputing device 100 b), or managing virtual machines 406 b, 406 c onthe computing device 100. In another embodiment, the tools stack 404includes customized applications for providing improved managementfunctionality to an administrator of a virtual machine farm. In someembodiments, at least one of the tools stack 404 and the controloperating system 405 include a management API that provides an interfacefor remotely configuring and controlling virtual machines 406 running ona computing device 100. In other embodiments, the control operatingsystem 405 communicates with the hypervisor 401 through the tools stack404.

In one embodiment, the hypervisor 401 executes a guest operating system410 within a virtual machine 406 created by the hypervisor 401. Inanother embodiment, the guest operating system 410 provides a user ofthe computing device 100 with access to resources within a computingenvironment. In still another embodiment, a resource includes a program,an application, a document, a file, a plurality of applications, aplurality of files, an executable program file, a desktop environment, acomputing environment, or other resource made available to a user of thecomputing device 100. In yet another embodiment, the resource may bedelivered to the computing device 100 via a plurality of access methodsincluding, but not limited to, conventional installation directly on thecomputing device 100, delivery to the computing device 100 via a methodfor application streaming, delivery to the computing device 100 ofoutput data generated by an execution of the resource on a secondcomputing device 100′ and communicated to the computing device 100 via apresentation layer protocol, delivery to the computing device 100 ofoutput data generated by an execution of the resource via a virtualmachine executing on a second computing device 100′, or execution from aremovable storage device connected to the computing device 100, such asa USB device, or via a virtual machine executing on the computing device100 and generating output data. In some embodiments, the computingdevice 100 transmits output data generated by the execution of theresource to another computing device 100′.

In one embodiment, the guest operating system 410, in conjunction withthe virtual machine on which it executes, forms a fully-virtualizedvirtual machine which is not aware that it is a virtual machine; such amachine may be referred to as a “Domain U HVM (Hardware Virtual Machine)virtual machine”. In another embodiment, a fully-virtualized machineincludes software emulating a Basic Input/Output System (BIOS) in orderto execute an operating system within the fully-virtualized machine. Instill another embodiment, a fully-virtualized machine may include adriver that provides functionality by communicating with the hypervisor401. In such an embodiment, the driver may be aware that it executeswithin a virtualized environment. In another embodiment, the guestoperating system 410, in conjunction with the virtual machine on whichit executes, forms a paravirtualized virtual machine, which is awarethat it is a virtual machine; such a machine may be referred to as a“Domain U PV virtual machine”. In another embodiment, a paravirtualizedmachine includes additional drivers that a fully-virtualized machinedoes not include. In still another embodiment, the paravirtualizedmachine includes the network back-end driver and the block back-enddriver included in a control operating system 405, as described above.

Referring now to FIG. 4B, a block diagram depicts one embodiment of aplurality of networked computing devices in a system in which at leastone physical host executes a virtual machine. In brief overview, thesystem includes a management component 404 and a hypervisor 401. Thesystem includes a plurality of computing devices 100, a plurality ofvirtual machines 406, a plurality of hypervisors 401, a plurality ofmanagement components referred to variously as tools stacks 404 ormanagement components 404, and a physical resource 421, 428. Theplurality of physical machines 100 may each be provided as computingdevices 100, described above in connection with FIGS. 1E-1H and 4A.

In greater detail, a physical disk 428 is provided by a computing device100 and stores at least a portion of a virtual disk 442. In someembodiments, a virtual disk 442 is associated with a plurality ofphysical disks 428. In one of these embodiments, one or more computingdevices 100 may exchange data with one or more of the other computingdevices 100 regarding processors and other physical resources availablein a pool of resources, allowing a hypervisor to manage a pool ofresources distributed across a plurality of physical computing devices.In some embodiments, a computing device 100 on which a virtual machine406 executes is referred to as a physical host 100 or as a host machine100.

The hypervisor executes on a processor on the computing device 100. Thehypervisor allocates, to a virtual disk, an amount of access to thephysical disk. In one embodiment, the hypervisor 401 allocates an amountof space on the physical disk. In another embodiment, the hypervisor 401allocates a plurality of pages on the physical disk. In someembodiments, the hypervisor provisions the virtual disk 442 as part of aprocess of initializing and executing a virtual machine 450.

In one embodiment, the management component 404 a is referred to as apool management component 404 a. In another embodiment, a managementoperating system 405 a, which may be referred to as a control operatingsystem 405 a, includes the management component. In some embodiments,the management component is referred to as a tools stack. In one ofthese embodiments, the management component is the tools stack 404described above in connection with FIG. 4A. In other embodiments, themanagement component 404 provides a user interface for receiving, from auser such as an administrator, an identification of a virtual machine406 to provision and/or execute. In still other embodiments, themanagement component 404 provides a user interface for receiving, from auser such as an administrator, the request for migration of a virtualmachine 406 b from one physical machine 100 to another. In furtherembodiments, the management component 404 a identifies a computingdevice 100 b on which to execute a requested virtual machine 406 d andinstructs the hypervisor 401 b on the identified computing device 100 bto execute the identified virtual machine; such a management componentmay be referred to as a pool management component.

Referring now to FIG. 4C, embodiments of a virtual application deliverycontroller or virtual appliance 450 are depicted. In brief overview, anyof the functionality and/or embodiments of the appliance 200 (e.g., anapplication delivery controller) described above in connection withFIGS. 2A and 2B may be deployed in any embodiment of the virtualizedenvironment described above in connection with FIGS. 4A and 4B. Insteadof the functionality of the application delivery controller beingdeployed in the form of an appliance 200, such functionality may bedeployed in a virtualized environment 400 on any computing device 100,such as a client 102, server 106 or appliance 200.

Referring now to FIG. 4C, a diagram of an embodiment of a virtualappliance 450 operating on a hypervisor 401 of a server 106 is depicted.As with the appliance 200 of FIGS. 2A and 2B, the virtual appliance 450may provide functionality for availability, performance, offload andsecurity. For availability, the virtual appliance may perform loadbalancing between layers 4 and 7 of the network and may also performintelligent service health monitoring. For performance increases vianetwork traffic acceleration, the virtual appliance may perform cachingand compression. To offload processing of any servers, the virtualappliance may perform connection multiplexing and pooling and/or SSLprocessing. For security, the virtual appliance may perform any of theapplication firewall functionality and SSL VPN function of appliance200.

Any of the modules of the appliance 200 as described in connection withFIG. 2A may be packaged, combined, designed or constructed in a form ofthe virtualized appliance delivery controller 450 deployable as one ormore software modules or components executable in a virtualizedenvironment 300 or non-virtualized environment on any server, such as anoff the shelf server. For example, the virtual appliance may be providedin the form of an installation package to install on a computing device.With reference to FIG. 2A, any of the cache manager 232, policy engine236, compression 238, encryption engine 234, packet engine 240, GUI 210,CLI 212, shell services 214 and health monitoring programs 216 may bedesigned and constructed as a software component or module to run on anyoperating system of a computing device and/or of a virtualizedenvironment 300. Instead of using the encryption processor 260,processor 262, memory 264 and network stack 267 of the appliance 200,the virtualized appliance 400 may use any of these resources as providedby the virtualized environment 400 or as otherwise available on theserver 106.

Still referring to FIG. 4C, and in brief overview, any one or morevServers 275A-275N may be in operation or executed in a virtualizedenvironment 400 of any type of computing device 100, such as any server106. Any of the modules or functionality of the appliance 200 describedin connection with FIG. 2B may be designed and constructed to operate ineither a virtualized or non-virtualized environment of a server. Any ofthe vServer 275, SSL VPN 280, Intranet UP 282, Switching 284, DNS 286,acceleration 288, App FW 280 and monitoring agent may be packaged,combined, designed or constructed in a form of application deliverycontroller 450 deployable as one or more software modules or componentsexecutable on a device and/or virtualized environment 400.

In some embodiments, a server may execute multiple virtual machines 406a-406 n in the virtualization environment with each virtual machinerunning the same or different embodiments of the virtual applicationdelivery controller 450. In some embodiments, the server may execute oneor more virtual appliances 450 on one or more virtual machines on a coreof a multi-core processing system. In some embodiments, the server mayexecute one or more virtual appliances 450 on one or more virtualmachines on each processor of a multiple processor device.

E. Systems and Methods for Providing A Multi-Core Architecture

In accordance with Moore's Law, the number of transistors that may beplaced on an integrated circuit may double approximately every twoyears. However, CPU speed increases may reach plateaus, for example CPUspeed has been around 3.5-4 GHz range since 2005. In some cases, CPUmanufacturers may not rely on CPU speed increases to gain additionalperformance. Some CPU manufacturers may add additional cores to theirprocessors to provide additional performance. Products, such as those ofsoftware and networking vendors, that rely on CPUs for performance gainsmay improve their performance by leveraging these multi-core CPUs. Thesoftware designed and constructed for a single CPU may be redesignedand/or rewritten to take advantage of a multi-threaded, parallelarchitecture or otherwise a multi-core architecture.

A multi-core architecture of the appliance 200, referred to as nCore ormulti-core technology, allows the appliance in some embodiments to breakthe single core performance barrier and to leverage the power ofmulti-core CPUs. In the previous architecture described in connectionwith FIG. 2A, a single network or packet engine is run. The multiplecores of the nCore technology and architecture allow multiple packetengines to run concurrently and/or in parallel. With a packet enginerunning on each core, the appliance architecture leverages theprocessing capacity of additional cores. In some embodiments, thisprovides up to a 7× increase in performance and scalability.

Illustrated in FIG. 5A are some embodiments of work, task, load ornetwork traffic distribution across one or more processor coresaccording to a type of parallelism or parallel computing scheme, such asfunctional parallelism, data parallelism or flow-based data parallelism.In brief overview, FIG. 5A illustrates embodiments of a multi-coresystem such as an appliance 200′ with n-cores, a total of cores numbers1 through N. In one embodiment, work, load or network traffic can bedistributed among a first core 505A, a second core 505B, a third core505C, a fourth core 505D, a fifth core 505E, a sixth core 505F, aseventh core 505G, and so on such that distribution is across all or twoor more of the n cores 505N (hereinafter referred to collectively ascores 505.). There may be multiple VIPs 275 each running on a respectivecore of the plurality of cores. There may be multiple packet engines 240each running on a respective core of the plurality of cores. Any of theapproaches used may lead to different, varying or similar work load orperformance level 515 across any of the cores. For a functionalparallelism approach, each core may run a different function of thefunctionalities provided by the packet engine, a VIP 275 or appliance200. In a data parallelism approach, data may be paralleled ordistributed across the cores based on the Network Interface Card (NIC)or VIP 275 receiving the data. In another data parallelism approach,processing may be distributed across the cores by distributing dataflows to each core.

In further detail to FIG. 5A, in some embodiments, load, work or networktraffic can be distributed among cores 505 according to functionalparallelism 500. Functional parallelism may be based on each coreperforming one or more respective functions. In some embodiments, afirst core may perform a first function while a second core performs asecond function. In functional parallelism approach, the functions to beperformed by the multi-core system are divided and distributed to eachcore according to functionality. In some embodiments, functionalparallelism may be referred to as task parallelism and may be achievedwhen each processor or core executes a different process or function onthe same or different data. The core or processor may execute the sameor different code. In some cases, different execution threads or codemay communicate with one another as they work. Communication may takeplace to pass data from one thread to the next as part of a workflow.

In some embodiments, distributing work across the cores 505 according tofunctional parallelism 500, can comprise distributing network trafficaccording to a particular function such as network input/outputmanagement (NW I/O) 510A, secure sockets layer (SSL) encryption anddecryption 510B and transmission control protocol (TCP) functions 510C.This may lead to a work, performance or computing load 515 based on avolume or level of functionality being used. In some embodiments,distributing work across the cores 505 according to data parallelism540, can comprise distributing an amount of work 515 based ondistributing data associated with a particular hardware or softwarecomponent. In some embodiments, distributing work across the cores 505according to flow-based data parallelism 520, can comprise distributingdata based on a context or flow such that the amount of work 515A-N oneach core may be similar, substantially equal or relatively evenlydistributed.

In the case of the functional parallelism approach, each core may beconfigured to run one or more functionalities of the plurality offunctionalities provided by the packet engine or VIP of the appliance.For example, core 1 may perform network I/O processing for the appliance200′ while core 2 performs TCP connection management for the appliance.Likewise, core 3 may perform SSL offloading while core 4 may performlayer 7 or application layer processing and traffic management. Each ofthe cores may perform the same function or different functions. Each ofthe cores may perform more than one function. Any of the cores may runany of the functionality or portions thereof identified and/or describedin conjunction with FIGS. 2A and 2B. In this the approach, the workacross the cores may be divided by function in either a coarse-grainedor fine-grained manner. In some cases, as illustrated in FIG. 5A,division by function may lead to different cores running at differentlevels of performance or load 515.

In the case of the functional parallelism approach, each core may beconfigured to run one or more functionalities of the plurality offunctionalities provided by the packet engine of the appliance. Forexample, core 1 may perform network I/O processing for the appliance200′ while core 2 performs TCP connection management for the appliance.Likewise, core 3 may perform SSL offloading while core 4 may performlayer 7 or application layer processing and traffic management. Each ofthe cores may perform the same function or different functions. Each ofthe cores may perform more than one function. Any of the cores may runany of the functionality or portions thereof identified and/or describedin conjunction with FIGS. 2A and 2B. In this the approach, the workacross the cores may be divided by function in either a coarse-grainedor fine-grained manner. In some cases, as illustrated in FIG. 5Adivision by function may lead to different cores running at differentlevels of load or performance.

The functionality or tasks may be distributed in any arrangement andscheme. For example, FIG. 5B illustrates a first core, Core 1 505A,processing applications and processes associated with network I/Ofunctionality 510A. Network traffic associated with network I/O, in someembodiments, can be associated with a particular port number. Thus,outgoing and incoming packets having a port destination associated withNW I/O 510A will be directed towards Core 1 505A which is dedicated tohandling all network traffic associated with the NW I/O port. Similarly,Core 2 505B is dedicated to handling functionality associated with SSLprocessing and Core 4 505D may be dedicated handling all TCP levelprocessing and functionality.

While FIG. 5A illustrates functions such as network I/O, SSL and TCP,other functions can be assigned to cores. These other functions caninclude any one or more of the functions or operations described herein.For example, any of the functions described in conjunction with FIGS. 2Aand 2B may be distributed across the cores on a functionality basis. Insome cases, a first VIP 275A may run on a first core while a second VIP275B with a different configuration may run on a second core. In someembodiments, each core 505 can handle a particular functionality suchthat each core 505 can handle the processing associated with thatparticular function. For example, Core 2 505B may handle SSL offloadingwhile Core 4 505D may handle application layer processing and trafficmanagement.

In other embodiments, work, load or network traffic may be distributedamong cores 505 according to any type and form of data parallelism 540.In some embodiments, data parallelism may be achieved in a multi-coresystem by each core performing the same task or functionally ondifferent pieces of distributed data. In some embodiments, a singleexecution thread or code controls operations on all pieces of data. Inother embodiments, different threads or instructions control theoperation, but may execute the same code. In some embodiments, dataparallelism is achieved from the perspective of a packet engine,vServers (VIPs) 275A-C, network interface cards (NIC) 542D-E and/or anyother networking hardware or software included on or associated with anappliance 200. For example, each core may run the same packet engine orVIP code or configuration but operate on different sets of distributeddata. Each networking hardware or software construct can receivedifferent, varying or substantially the same amount of data, and as aresult may have varying, different or relatively the same amount of load515.

In the case of a data parallelism approach, the work may be divided upand distributed based on VIPs, NICs and/or data flows of the VIPs orNICs. In one of these approaches, the work of the multi-core system maybe divided or distributed among the VIPs by having each VIP work on adistributed set of data. For example, each core may be configured to runone or more VIPs. Network traffic may be distributed to the core foreach VIP handling that traffic. In another of these approaches, the workof the appliance may be divided or distributed among the cores based onwhich NIC receives the network traffic. For example, network traffic ofa first NIC may be distributed to a first core while network traffic ofa second NIC may be distributed to a second core. In some cases, a coremay process data from multiple NICs.

While FIG. 5A illustrates a single vServer associated with a single core505, as is the case for VIP1 275A, VIP2 275B and VIP3 275C. In someembodiments, a single vServer can be associated with one or more cores505. In contrast, one or more vServers can be associated with a singlecore 505. Associating a vServer with a core 505 may include that core505 to process all functions associated with that particular vServer. Insome embodiments, each core executes a VIP having the same code andconfiguration. In other embodiments, each core executes a VIP having thesame code but different configuration. In some embodiments, each coreexecutes a VIP having different code and the same or differentconfiguration.

Like vServers, NICs can also be associated with particular cores 505. Inmany embodiments, NICs can be connected to one or more cores 505 suchthat when a NIC receives or transmits data packets, a particular core505 handles the processing involved with receiving and transmitting thedata packets. In one embodiment, a single NIC can be associated with asingle core 505, as is the case with NIC1 542D and NIC2 542E. In otherembodiments, one or more NICs can be associated with a single core 505.In other embodiments, a single NIC can be associated with one or morecores 505. In these embodiments, load could be distributed amongst theone or more cores 505 such that each core 505 processes a substantiallysimilar amount of load. A core 505 associated with a NIC may process allfunctions and/or data associated with that particular NIC.

While distributing work across cores based on data of VIPs or NICs mayhave a level of independency, in some embodiments, this may lead tounbalanced use of cores as illustrated by the varying loads 515 of FIG.5A.

In some embodiments, load, work or network traffic can be distributedamong cores 505 based on any type and form of data flow. In another ofthese approaches, the work may be divided or distributed among coresbased on data flows. For example, network traffic between a client and aserver traversing the appliance may be distributed to and processed byone core of the plurality of cores. In some cases, the core initiallyestablishing the session or connection may be the core for which networktraffic for that session or connection is distributed. In someembodiments, the data flow is based on any unit or portion of networktraffic, such as a transaction, a request/response communication ortraffic originating from an application on a client. In this manner andin some embodiments, data flows between clients and servers traversingthe appliance 200′ may be distributed in a more balanced manner than theother approaches.

In flow-based data parallelism 520, distribution of data is related toany type of flow of data, such as request/response pairings,transactions, sessions, connections or application communications. Forexample, network traffic between a client and a server traversing theappliance may be distributed to and processed by one core of theplurality of cores. In some cases, the core initially establishing thesession or connection may be the core for which network traffic for thatsession or connection is distributed. The distribution of data flow maybe such that each core 505 carries a substantially equal or relativelyevenly distributed amount of load, data or network traffic.

In some embodiments, the data flow is based on any unit or portion ofnetwork traffic, such as a transaction, a request/response communicationor traffic originating from an application on a client. In this mannerand in some embodiments, data flows between clients and serverstraversing the appliance 200′ may be distributed in a more balancedmanner than the other approached. In one embodiment, data flow can bedistributed based on a transaction or a series of transactions. Thistransaction, in some embodiments, can be between a client and a serverand can be characterized by an IP address or other packet identifier.For example, Core 1 505A can be dedicated to transactions between aparticular client and a particular server, therefore the load 515A onCore 1 505A may be comprised of the network traffic associated with thetransactions between the particular client and server. Allocating thenetwork traffic to Core 1 505A can be accomplished by routing all datapackets originating from either the particular client or server to Core1 505A.

While work or load can be distributed to the cores based in part ontransactions, in other embodiments load or work can be allocated on aper packet basis. In these embodiments, the appliance 200 can interceptdata packets and allocate them to a core 505 having the least amount ofload. For example, the appliance 200 could allocate a first incomingdata packet to Core 1 505A because the load 515A on Core 1 is less thanthe load 515B-N on the rest of the cores 505B-N. Once the first datapacket is allocated to Core 1 505A, the amount of load 515A on Core 1505A is increased proportional to the amount of processing resourcesneeded to process the first data packet. When the appliance 200intercepts a second data packet, the appliance 200 will allocate theload to Core 4 505D because Core 4 505D has the second least amount ofload. Allocating data packets to the core with the least amount of loadcan, in some embodiments, ensure that the load 515A-N distributed toeach core 505 remains substantially equal.

In other embodiments, load can be allocated on a per unit basis where asection of network traffic is allocated to a particular core 505. Theabove-mentioned example illustrates load balancing on a per/packetbasis. In other embodiments, load can be allocated based on a number ofpackets such that every 10, 100 or 1000 packets are allocated to thecore 505 having the least amount of load. The number of packetsallocated to a core 505 can be a number determined by an application,user or administrator and can be any number greater than zero. In stillother embodiments, load can be allocated based on a time metric suchthat packets are distributed to a particular core 505 for apredetermined amount of time. In these embodiments, packets can bedistributed to a particular core 505 for five milliseconds or for anyperiod of time determined by a user, program, system, administrator orotherwise. After the predetermined time period elapses, data packets aretransmitted to a different core 505 for the predetermined period oftime.

Flow-based data parallelism methods for distributing work, load ornetwork traffic among the one or more cores 505 can comprise anycombination of the above-mentioned embodiments. These methods can becarried out by any part of the appliance 200, by an application or setof executable instructions executing on one of the cores 505, such asthe packet engine, or by any application, program or agent executing ona computing device in communication with the appliance 200.

The functional and data parallelism computing schemes illustrated inFIG. 5A can be combined in any manner to generate a hybrid parallelismor distributed processing scheme that encompasses function parallelism500, data parallelism 540, flow-based data parallelism 520 or anyportions thereof. In some cases, the multi-core system may use any typeand form of load balancing schemes to distribute load among the one ormore cores 505. The load balancing scheme may be used in any combinationwith any of the functional and data parallelism schemes or combinationsthereof.

Illustrated in FIG. 5B is an embodiment of a multi-core system 545,which may be any type and form of one or more systems, appliances,devices or components. This system 545, in some embodiments, can beincluded within an appliance 200 having one or more processing cores505A-N. The system 545 can further include one or more packet engines(PE) or packet processing engines (PPE) 548A-N communicating with amemory bus 556. The memory bus may be used to communicate with the oneor more processing cores 505A-N. Also included within the system 545 canbe one or more network interface cards (NIC) 552 and a flow distributor550 which can further communicate with the one or more processing cores505A-N. The flow distributor 550 can comprise a Receive Side Scaler(RSS) or Receive Side Scaling (RSS) module 560.

Further referring to FIG. 5B, and in more detail, in one embodiment thepacket engine(s) 548A-N can comprise any portion of the appliance 200described herein, such as any portion of the appliance described inFIGS. 2A and 2B. The packet engine(s) 548A-N can, in some embodiments,comprise any of the following elements: the packet engine 240, a networkstack 267; a cache manager 232; a policy engine 236; a compressionengine 238; an encryption engine 234; a GUI 210; a CLI 212; shellservices 214; monitoring programs 216; and any other software orhardware element able to receive data packets from one of either thememory bus 556 or the one of more cores 505A-N. In some embodiments, thepacket engine(s) 548A-N can comprise one or more vServers 275A-N, or anyportion thereof. In other embodiments, the packet engine(s) 548A-N canprovide any combination of the following functionalities: SSL VPN 280;Intranet UP 282; switching 284; DNS 286; packet acceleration 288; App FW280; monitoring such as the monitoring provided by a monitoring agent197; functionalities associated with functioning as a TCP stack; loadbalancing; SSL offloading and processing; content switching; policyevaluation; caching; compression; encoding; decompression; decoding;application firewall functionalities; XML processing and acceleration;and SSL VPN connectivity.

The packet engine(s) 548A-N can, in some embodiments, be associated witha particular server, user, client or network. When a packet engine 548becomes associated with a particular entity, that packet engine 548 canprocess data packets associated with that entity. For example, should apacket engine 548 be associated with a first user, that packet engine548 will process and operate on packets generated by the first user, orpackets having a destination address associated with the first user.Similarly, the packet engine 548 may choose not to be associated with aparticular entity such that the packet engine 548 can process andotherwise operate on any data packets not generated by that entity ordestined for that entity.

In some instances, the packet engine(s) 548A-N can be configured tocarry out the any of the functional and/or data parallelism schemesillustrated in FIG. 5A. In these instances, the packet engine(s) 548A-Ncan distribute functions or data among the processing cores 505A-N sothat the distribution is according to the parallelism or distributionscheme. In some embodiments, a single packet engine(s) 548A-N carriesout a load balancing scheme, while in other embodiments one or morepacket engine(s) 548A-N carry out a load balancing scheme. Each core505A-N, in one embodiment, can be associated with a particular packetengine 548 such that load balancing can be carried out by the packetengine. Load balancing may in this embodiment, require that each packetengine 548A-N associated with a core 505 communicate with the otherpacket engines associated with cores so that the packet engines 548A-Ncan collectively determine where to distribute load. One embodiment ofthis process can include an arbiter that receives votes from each packetengine for load. The arbiter can distribute load to each packet engine548A-N based in part on the age of the engine's vote and in some cases apriority value associated with the current amount of load on an engine'sassociated core 505.

Any of the packet engines running on the cores may run in user mode,kernel or any combination thereof. In some embodiments, the packetengine operates as an application or program running is user orapplication space. In these embodiments, the packet engine may use anytype and form of interface to access any functionality provided by thekernel. In some embodiments, the packet engine operates in kernel modeor as part of the kernel. In some embodiments, a first portion of thepacket engine operates in user mode while a second portion of the packetengine operates in kernel mode. In some embodiments, a first packetengine on a first core executes in kernel mode while a second packetengine on a second core executes in user mode. In some embodiments, thepacket engine or any portions thereof operates on or in conjunction withthe NIC or any drivers thereof.

In some embodiments the memory bus 556 can be any type and form ofmemory or computer bus. While a single memory bus 556 is depicted inFIG. 5B, the system 545 can comprise any number of memory buses 556. Inone embodiment, each packet engine 548 can be associated with one ormore individual memory buses 556.

The NIC 552 can in some embodiments be any of the network interfacecards or mechanisms described herein. The NIC 552 can have any number ofports. The NIC can be designed and constructed to connect to any typeand form of network 104. While a single NIC 552 is illustrated, thesystem 545 can comprise any number of NICs 552. In some embodiments,each core 505A-N can be associated with one or more single NICs 552.Thus, each core 505 can be associated with a single NIC 552 dedicated toa particular core 505. The cores 505A-N can comprise any of theprocessors described herein. Further, the cores 505A-N can be configuredaccording to any of the core 505 configurations described herein. Stillfurther, the cores 505A-N can have any of the core 505 functionalitiesdescribed herein. While FIG. 5B illustrates seven cores 505A-G, anynumber of cores 505 can be included within the system 545. Inparticular, the system 545 can comprise “N” cores, where “N” is a wholenumber greater than zero.

A core may have or use memory that is allocated or assigned for use tothat core. The memory may be considered private or local memory of thatcore and only accessible by that core. A core may have or use memorythat is shared or assigned to multiple cores. The memory may beconsidered public or shared memory that is accessible by more than onecore. A core may use any combination of private and public memory. Withseparate address spaces for each core, some level of coordination iseliminated from the case of using the same address space. With aseparate address space, a core can perform work on information and datain the core's own address space without worrying about conflicts withother cores. Each packet engine may have a separate memory pool for TCPand/or SSL connections.

Further referring to FIG. 5B, any of the functionality and/orembodiments of the cores 505 described above in connection with FIG. 5Acan be deployed in any embodiment of the virtualized environmentdescribed above in connection with FIGS. 4A and 4B. Instead of thefunctionality of the cores 505 being deployed in the form of a physicalprocessor 505, such functionality may be deployed in a virtualizedenvironment 400 on any computing device 100, such as a client 102,server 106 or appliance 200. In other embodiments, instead of thefunctionality of the cores 505 being deployed in the form of anappliance or a single device, the functionality may be deployed acrossmultiple devices in any arrangement. For example, one device maycomprise two or more cores and another device may comprise two or morecores. For example, a multi-core system may include a cluster ofcomputing devices, a server farm or network of computing devices. Insome embodiments, instead of the functionality of the cores 505 beingdeployed in the form of cores, the functionality may be deployed on aplurality of processors, such as a plurality of single core processors.

In one embodiment, the cores 505 may be any type and form of processor.In some embodiments, a core can function substantially similar to anyprocessor or central processing unit described herein. In someembodiment, the cores 505 may comprise any portion of any processordescribed herein. While FIG. 5A illustrates seven cores, there can existany “N” number of cores within an appliance 200, where “N” is any wholenumber greater than one. In some embodiments, the cores 505 can beinstalled within a common appliance 200, while in other embodiments thecores 505 can be installed within one or more appliance(s) 200communicatively connected to one another. The cores 505 can in someembodiments comprise graphics processing software, while in otherembodiments the cores 505 provide general processing capabilities. Thecores 505 can be installed physically near each other and/or can becommunicatively connected to each other. The cores may be connected byany type and form of bus or subsystem physically and/or communicativelycoupled to the cores for transferring data between to, from and/orbetween the cores.

While each core 505 can comprise software for communicating with othercores, in some embodiments a core manager (not shown) can facilitatecommunication between each core 505. In some embodiments, the kernel mayprovide core management. The cores may interface or communicate witheach other using a variety of interface mechanisms. In some embodiments,core to core messaging may be used to communicate between cores, such asa first core sending a message or data to a second core via a bus orsubsystem connecting the cores. In some embodiments, cores maycommunicate via any type and form of shared memory interface. In oneembodiment, there may be one or more memory locations shared among allthe cores. In some embodiments, each core may have separate memorylocations shared with each other core. For example, a first core mayhave a first shared memory with a second core and a second share memorywith a third core. In some embodiments, cores may communicate via anytype of programming or API, such as function calls via the kernel. Insome embodiments, the operating system may recognize and supportmultiple core devices and provide interfaces and API for inter-corecommunications.

The flow distributor 550 can be any application, program, library,script, task, service, process or any type and form of executableinstructions executing on any type and form of hardware. In someembodiments, the flow distributor 550 may comprise any design andconstruction of circuitry to perform any of the operations and functionsdescribed herein. In some embodiments, the flow distributor distributes,forwards, routes, controls and/or manages the distribution of datapackets among the cores 505 and/or packet engine or VIPs running on thecores. The flow distributor 550, in some embodiments, can be referred toas an interface master. In one embodiment, the flow distributor 550comprises a set of executable instructions executing on a core orprocessor of the appliance 200. In another embodiment, the flowdistributor 550 comprises a set of executable instructions executing ona computing machine in communication with the appliance 200. In someembodiments, the flow distributor 550 comprises a set of executableinstructions executing on a NIC, such as firmware. In still otherembodiments, the flow distributor 550 comprises any combination ofsoftware and hardware to distribute data packets among cores orprocessors. In one embodiment, the flow distributor 550 executes on atleast one of the cores 505A-N, while in other embodiments a separateflow distributor 550 assigned to each core 505A-N executes on anassociated core 505A-N. The flow distributor may use any type and formof statistical or probabilistic algorithms or decision making to balancethe flows across the cores. The hardware of the appliance, such as aNIC, or the kernel may be designed and constructed to support sequentialoperations across the NICs and/or cores.

In embodiments where the system 545 comprises one or more flowdistributors 550, each flow distributor 550 can be associated with aprocessor 505 or a packet engine 548. The flow distributors 550 cancomprise an interface mechanism that allows each flow distributor 550 tocommunicate with the other flow distributors 550 executing within thesystem 545. In one instance, the one or more flow distributors 550 candetermine how to balance load by communicating with each other. Thisprocess can operate substantially similarly to the process describedabove for submitting votes to an arbiter which then determines whichflow distributor 550 should receive the load. In other embodiments, afirst flow distributor 550′ can identify the load on an associated coreand determine whether to forward a first data packet to the associatedcore based on any of the following criteria: the load on the associatedcore is above a predetermined threshold; the load on the associated coreis below a predetermined threshold; the load on the associated core isless than the load on the other cores; or any other metric that can beused to determine where to forward data packets based in part on theamount of load on a processor.

The flow distributor 550 can distribute network traffic among the cores505 according to a distribution, computing or load balancing scheme suchas those described herein. In one embodiment, the flow distributor candistribute network traffic according to any one of a functionalparallelism distribution scheme 550, a data parallelism loaddistribution scheme 540, a flow-based data parallelism distributionscheme 520, or any combination of these distribution scheme or any loadbalancing scheme for distributing load among multiple processors. Theflow distributor 550 can therefore act as a load distributor by takingin data packets and distributing them across the processors according toan operative load balancing or distribution scheme. In one embodiment,the flow distributor 550 can comprise one or more operations, functionsor logic to determine how to distribute packers, work or loadaccordingly. In still other embodiments, the flow distributor 550 cancomprise one or more sub operations, functions or logic that canidentify a source address and a destination address associated with adata packet, and distribute packets accordingly.

In some embodiments, the flow distributor 550 can comprise areceive-side scaling (RSS) network driver, module 560 or any type andform of executable instructions which distribute data packets among theone or more cores 505. The RSS module 560 can comprise any combinationof hardware and software, In some embodiments, the RSS module 560 worksin conjunction with the flow distributor 550 to distribute data packetsacross the cores 505A-N or among multiple processors in amulti-processor network. The RSS module 560 can execute within the NIC552 in some embodiments, and in other embodiments can execute on any oneof the cores 505.

In some embodiments, the RSS module 560 uses the MICROSOFTreceive-side-scaling (RSS) scheme. In one embodiment, RSS is a MicrosoftScalable Networking initiative technology that enables receiveprocessing to be balanced across multiple processors in the system whilemaintaining in-order delivery of the data. The RSS may use any type andform of hashing scheme to determine a core or processor for processing anetwork packet. In other embodiments, the RSS module 560 may employ adifferent RSS scheme than the MICROSOFT scheme. For example, theMICROSOFT RSS scheme may apply to a maximum of 64 processors or cores.In embodiments where a greater number of cores are used, the RSS module560 may employ a different RSS scheme, configured to distribute packetsacross any number of cores up to 128, 256, 512, or any other number.

The RSS module 560 can apply any type and form of hash function such asthe Toeplitz hash function. The hash function may be applied to the hashtype or any of the sequence of values. The hash function may be a securehash of any security level or one that is otherwise cryptographicallysecure. The hash function may use a hash key. The size of the key isdependent upon the hash function. For the Toeplitz hash, the size may be40 bytes for IPv6 and 16 bytes for IPv4. In some embodiments, discussedin more detail below, the hash key may be generated by a random numbergenerator. In other embodiments, the hash key may be selected from apredetermine list of hash keys. In many embodiments, the hash key may begenerated or selected when the appliance boots. In other embodiments,the hash key may be generated or selected once per week, once per day,once per hour, or any other interval of time.

The hash function may be designed and constructed based on any one ormore criteria or design goals. In some embodiments, a hash function maybe used that provides an even distribution of hash result for differenthash inputs and different hash types, including TCP/IPv4, TCP/IPv6,IPv4, and IPv6 headers. In some embodiments, a hash function may be usedthat provides a hash result that is evenly distributed when a smallnumber of buckets are present (for example, two or four). In someembodiments, hash function may be used that provides a hash result thatis randomly distributed when a large number of buckets were present (forexample, 64 or 128 buckets). In some embodiments, the hash function isdetermined based on a level of computational or resource usage. In someembodiments, the hash function is determined based on ease or difficultyof implementing the hash in hardware. In some embodiments, the hashfunction is determined based on the ease or difficulty of a maliciousremote host to send packets that would all hash to the same bucket.

The RSS may generate hashes from any type and form of input, such as asequence of values. This sequence of values can include any portion ofthe network packet, such as any header, field or payload of networkpacket, or portions thereof. In some embodiments, the input to the hashmay be referred to as a hash type and include any tuples of informationassociated with a network packet or data flow, such as any of thefollowing: a four tuple comprising at least two IP addresses and twoports; a four tuple comprising any four sets of values; a six tuple; atwo tuple; and/or any other sequence of numbers or values. The followingare example of hash types that may be used by RSS:

-   -   4-tuple of source TCP Port, source IP version 4 (IPv4) address,        destination TCP Port, and destination IPv4 address.    -   4-tuple of source TCP Port, source IP version 6 (IPv6) address,        destination TCP Port, and destination IPv6 address.    -   2-tuple of source IPv4 address, and destination IPv4 address.    -   2-tuple of source IPv6 address, and destination IPv6 address.    -   2-tuple of source IPv6 address, and destination IPv6 address,        including support for parsing IPv6 extension headers.

The hash result or any portion thereof may used to identify a core orentity, such as a packet engine or VIP, for distributing a networkpacket. In some embodiments, one or more hash bits or mask are appliedto the hash result. The hash bit or mask may be any number of bits orbytes. A NIC may support any number of bits, such as six or seven bits.The network stack may set the actual number of bits to be used duringinitialization. The number may be between 1 and 7, inclusive. In otherembodiments, the number may be higher, such as 8 bits or more. In manyembodiments, the number of bits of the mask may be selected based on thenumber of processors or cores in a system. For example, 6 bits may beused in a system supporting less than 2̂6 or 64 processors or cores,while 7 bits may be used in a system supporting up to 2̂7 or 128processors or cores.

The hash result may be used to identify the core or entity via any typeand form of table, such as a bucket table or indirection table. In someembodiments, the number of hash-result bits are used to index into thetable. The range of the hash mask may effectively define the size of theindirection table. Any portion of the hash result or the hast resultitself may be used to index the indirection table. The values in thetable may identify any of the cores or processor, such as by a core orprocessor identifier. In some embodiments, all of the cores of themulti-core system are identified in the table. In other embodiments, aport of the cores of the multi-core system are identified in the table.The indirection table may comprise any number of buckets that may beindexed by a hash mask, such as 2 to 128 buckets. Each bucket maycomprise a range of index values that identify a core or processor. Insome embodiments, the flow controller and/or RSS module may rebalancethe network rebalance the network load by changing the indirectiontable.

In some embodiments, the multi-core system 575 does not include a RSSdriver or RSS module 560. In some of these embodiments, a softwaresteering module (not shown) or a software embodiment of the RSS modulewithin the system can operate in conjunction with or as part of the flowdistributor 550 to steer packets to cores 505 within the multi-coresystem 575.

The flow distributor 550, in some embodiments, executes within anymodule or program on the appliance 200, on any one of the cores 505 andon any one of the devices or components included within the multi-coresystem 575. In some embodiments, the flow distributor 550′ can executeon the first core 505A, while in other embodiments the flow distributor550″ can execute on the NIC 552. In still other embodiments, an instanceof the flow distributor 550′ can execute on each core 505 included inthe multi-core system 575. In this embodiment, each instance of the flowdistributor 550′ can communicate with other instances of the flowdistributor 550′ to forward packets back and forth across the cores 505.There exist situations where a response to a request packet may not beprocessed by the same core, i.e. the first core processes the requestwhile the second core processes the response. In these situations, theinstances of the flow distributor 550′ can intercept the packet andforward it to the desired or correct core 505, i.e. a flow distributorinstance 550′ can forward the response to the first core. Multipleinstances of the flow distributor 550′ can execute on any number ofcores 505 and any combination of cores 505.

The flow distributor may operate responsive to any one or more rules orpolicies. The rules may identify a core or packet processing engine toreceive a network packet, data or data flow. The rules may identify anytype and form of tuple information related to a network packet, such asa 4-tuple of source and destination IP address and source anddestination ports. Based on a received packet matching the tuplespecified by the rule, the flow distributor may forward the packet to acore or packet engine. In some embodiments, the packet is forwarded to acore via shared memory and/or core to core messaging.

Although FIG. 5B illustrates the flow distributor 550 as executingwithin the multi-core system 575, in some embodiments the flowdistributor 550 can execute on a computing device or appliance remotelylocated from the multi-core system 575. In such an embodiment, the flowdistributor 550 can communicate with the multi-core system 575 to takein data packets and distribute the packets across the one or more cores505. The flow distributor 550 can, in one embodiment, receive datapackets destined for the appliance 200, apply a distribution scheme tothe received data packets and distribute the data packets to the one ormore cores 505 of the multi-core system 575. In one embodiment, the flowdistributor 550 can be included in a router or other appliance such thatthe router can target particular cores 505 by altering meta dataassociated with each packet so that each packet is targeted towards asub-node of the multi-core system 575. In such an embodiment, CISCO'svn-tag mechanism can be used to alter or tag each packet with theappropriate meta data.

Illustrated in FIG. 5C is an embodiment of a multi-core system 575comprising one or more processing cores 505A-N. In brief overview, oneof the cores 505 can be designated as a control core 505A and can beused as a control plane 570 for the other cores 505. The other cores maybe secondary cores which operate in a data plane while the control coreprovides the control plane. The cores 505A-N may share a global cache580. While the control core provides a control plane, the other cores inthe multi-core system form or provide a data plane. These cores performdata processing functionality on network traffic while the controlprovides initialization, configuration and control of the multi-coresystem.

Further referring to FIG. 5C, and in more detail, the cores 505A-N aswell as the control core 505A can be any processor described herein.Furthermore, the cores 505A-N and the control core 505A can be anyprocessor able to function within the system 575 described in FIG. 5C.Still further, the cores 505A-N and the control core 505A can be anycore or group of cores described herein. The control core may be adifferent type of core or processor than the other cores. In someembodiments, the control may operate a different packet engine or have apacket engine configured differently than the packet engines of theother cores.

Any portion of the memory of each of the cores may be allocated to orused for a global cache that is shared by the cores. In brief overview,a predetermined percentage or predetermined amount of each of the memoryof each core may be used for the global cache. For example, 50% of eachmemory of each code may be dedicated or allocated to the shared globalcache. That is, in the illustrated embodiment, 2 GB of each coreexcluding the control plane core or core 1 may be used to form a 28 GBshared global cache. The configuration of the control plane such as viathe configuration services may determine the amount of memory used forthe shared global cache. In some embodiments, each core may provide adifferent amount of memory for use by the global cache. In otherembodiments, any one core may not provide any memory or use the globalcache. In some embodiments, any of the cores may also have a local cachein memory not allocated to the global shared memory. Each of the coresmay store any portion of network traffic to the global shared cache.Each of the cores may check the cache for any content to use in arequest or response. Any of the cores may obtain content from the globalshared cache to use in a data flow, request or response.

The global cache 580 can be any type and form of memory or storageelement, such as any memory or storage element described herein. In someembodiments, the cores 505 may have access to a predetermined amount ofmemory (i.e. 32 GB or any other memory amount commensurate with thesystem 575). The global cache 580 can be allocated from thatpredetermined amount of memory while the rest of the available memorycan be allocated among the cores 505. In other embodiments, each core505 can have a predetermined amount of memory. The global cache 580 cancomprise an amount of the memory allocated to each core 505. This memoryamount can be measured in bytes, or can be measured as a percentage ofthe memory allocated to each core 505. Thus, the global cache 580 cancomprise 1 GB of memory from the memory associated with each core 505,or can comprise 20 percent or one-half of the memory associated witheach core 505. In some embodiments, only a portion of the cores 505provide memory to the global cache 580, while in other embodiments theglobal cache 580 can comprise memory not allocated to the cores 505.

Each core 505 can use the global cache 580 to store network traffic orcache data. In some embodiments, the packet engines of the core use theglobal cache to cache and use data stored by the plurality of packetengines. For example, the cache manager of FIG. 2A and cachefunctionality of FIG. 2B may use the global cache to share data foracceleration. For example, each of the packet engines may storeresponses, such as HTML data, to the global cache. Any of the cachemanagers operating on a core may access the global cache to servercaches responses to client requests.

In some embodiments, the cores 505 can use the global cache 580 to storea port allocation table which can be used to determine data flow basedin part on ports. In other embodiments, the cores 505 can use the globalcache 580 to store an address lookup table or any other table or listthat can be used by the flow distributor to determine where to directincoming and outgoing data packets. The cores 505 can, in someembodiments read from and write to cache 580, while in other embodimentsthe cores 505 can only read from or write to cache 580. The cores mayuse the global cache to perform core to core communications.

The global cache 580 may be sectioned into individual memory sectionswhere each section can be dedicated to a particular core 505. In oneembodiment, the control core 505A can receive a greater amount ofavailable cache, while the other cores 505 can receiving varying amountsor access to the global cache 580.

In some embodiments, the system 575 can comprise a control core 505A.While FIG. 5C illustrates core 1 505A as the control core, the controlcore can be any core within the appliance 200 or multi-core system.Further, while only a single control core is depicted, the system 575can comprise one or more control cores each having a level of controlover the system. In some embodiments, one or more control cores can eachcontrol a particular aspect of the system 575. For example, one core cancontrol deciding which distribution scheme to use, while another corecan determine the size of the global cache 580.

The control plane of the multi-core system may be the designation andconfiguration of a core as the dedicated management core or as a mastercore. This control plane core may provide control, management andcoordination of operation and functionality the plurality of cores inthe multi-core system. This control plane core may provide control,management and coordination of allocation and use of memory of thesystem among the plurality of cores in the multi-core system, includinginitialization and configuration of the same. In some embodiments, thecontrol plane includes the flow distributor for controlling theassignment of data flows to cores and the distribution of networkpackets to cores based on data flows. In some embodiments, the controlplane core runs a packet engine and in other embodiments, the controlplane core is dedicated to management and control of the other cores ofthe system.

The control core 505A can exercise a level of control over the othercores 505 such as determining how much memory should be allocated toeach core 505 or determining which core 505 should be assigned to handlea particular function or hardware/software entity. The control core505A, in some embodiments, can exercise control over those cores 505within the control plan 570. Thus, there can exist processors outside ofthe control plane 570 which are not controlled by the control core 505A.Determining the boundaries of the control plane 570 can includemaintaining, by the control core 505A or agent executing within thesystem 575, a list of those cores 505 controlled by the control core505A. The control core 505A can control any of the following:initialization of a core; determining when a core is unavailable;re-distributing load to other cores 505 when one core fails; determiningwhich distribution scheme to implement; determining which core shouldreceive network traffic; determining how much cache should be allocatedto each core; determining whether to assign a particular function orelement to a particular core; determining whether to permit cores tocommunicate with one another; determining the size of the global cache580; and any other determination of a function, configuration oroperation of the cores within the system 575.

F. Systems and Methods for Providing Analytics from an IntermediaryDevice

Referring now to FIGS. 6A and 6B, systems and methods are described forproviding network analytics by an inline device intermediary to aplurality of clients and servers, such as any embodiments of theappliance described herein. While managing any of the network trafficbetween the clients and the servers, the inline intermediary device mayprovide network analytics and metrics on the network traffic traversingthe appliance. The intermediary device may be designed and constructedto perform any of the desired traffic management and applicationdelivery control and management and also implement a network analyticssystem. The inline intermediary device can perform any of the followingfunctions: remove network inefficiencies; accelerate the transmission ofdata over the network; secure and protect data as the data istransmitted across the network; and be flexible enough to obtain andanalyze any number of metrics. The inline device can remove networkinefficiencies by performing compression and SSL and server offloading.The inline device can also accelerate the transmission of data by havingdeep application insight. The inline device can also secure and protectinformation transmitted over the network by executing all applicationsand logic on bare metal. Furthermore, the inline device can be flexiblebecause inline device has a rich statistics infrastructure like anexpressive policy engine. Using existing hardware to implement a networkanalytics solution can take advantage of an existing hardware footprintand can be used to highlight trends and outliers while being used totroubleshoot problems. This is more efficient than using a second devicethat has to tap into or receive mirrored traffic from the inline deviceto perform such network analytics.

Referring now to FIG. 6A, illustrated is an embodiment of a packetprocessing device 620 intermediary to a plurality of clients 102 a-102 nin a network 104 and one or more servers 106 a-106 n in a network 104′.The packet processing device 620, as illustrated in FIG. 6A,incorporates a packet processing engine 240 and an analytics engine 650.The analytics engine 650 may use a flow identifier 610 to identifystreams of network packets within the network traffic traversing andmanaged by the device 210. The analytic engine may use a collector 660to collect metrics for the streams of network packets identified by theflow identifier. The packet processing device 620 manages networktraffic between the plurality of clients 102 and the one or more servers106. For example, the packet processing device 620 may use a packetprocessing engine 240 to actively participate in communication flowsthrough the device, i.e., streams of network packets arriving to, ordeparting from, the packet processing device 620. While managing suchnetwork traffic, the packet processing device provides network metricsfor selected streams of network packets in the managed network traffic.

The packet processing device 620 may function in a network environmentsimilar to those described in relation to FIGS. 1A-1C. The packetprocessing device 620 may be an embodiment of an appliance 200. Thepacket processing device 620 may be a router or other computing devices,such as a desktop computer, server, rack-mount server, blade server, orany other type and form of computing device. The packet processingdevice 620 may be a single processor computing device or amulti-processor computing device. A processor used in the packetprocessing device 620 may be a single or multi-core processor. Thepacket processing device may include a virtualized environment 400, suchas those described in connection with FIGS. 4A-4C.

The packet processing engine may include any of embodiments of thepacket processing engine described herein. In some embodiments, thepacket processing engine may comprise a virtualized packet processingengine 450 such as any of the embodiments described in connection withFIGS. 4A-4C. In some embodiments, the packet processing engine maycomprise any embodiments of the packet processing engine 548 designedand constructed for execution and use in a multi-core system, such asthose described in connection with FIGS. 5A-5C.

In view of any embodiments of the packet processing engine describedherein, the packet processing engine may comprise or interface to apolicy engine, such as a policy engine 195 or policy engine 236. Thepolicy engine may be designed and constructed to received configurationof a policy, configure or specify and apply, and apply or execute one ormore policies in applying any of the network metrics and analysisfunctionality described herein. The analytics engine may operateresponsive to the policy engine and one or more policies. A policy mayidentify the type of metrics to collect. A policy may identify the flowidentifier for a stream of network packets for which to collect orprovide metrics. The analytics engine may identify flows or streams ofnetwork packets responsive to one or more policies. The analytics enginemay collect data from streams of network packets responsive to one ormore policies. The analytics engine may analyze data and determinemetrics from the collected data responsive to one or more policies.

The analytics engine 650 may comprise an application, program, library,service, process, task or any type and form of executable instructionsexecuting on a device, such as the packet processing device. In someembodiments, the packet processing engine incorporates or includes theanalytics engine. In these embodiments, the analytics engine may collectdata and perform network analytics and metrics on the network data viathe same memory and/or data structures or programming constructs thatthe packet processing engine uses for network data. In some embodiments,the packet processing engine interfaces to or communicates with theanalytics engine. In some of these embodiments, the analytics engine mayreceive a copy of or mirror of portions of flow or stream of networkpackets from the packet processing engine and process these copies inthe memory of the analytics engine using data structures and/orprogramming constructs of the analytics engine.

The analytics engine may be designed and constructed not to interferewith or impede the operation of the packet processing engine. Theanalytics engine may be designed and constructed not to interfere withor impede the flow of network traffic between the clients and theservers or otherwise traversing the packet processing device. Theanalytics engine may be designed and constructed not to slow down ordecrease the performance of the packet processing engine while thepacket processing engine manages network traffic between clients andservers. The analytics engine may be designed and constructed not tochange the operation and/or performance of the packet processing enginewhile the packet processing engine manages network traffic betweenclients and servers.

The analytics engine collects metrics and provides analytics on one ormore streams of network packets, or communication flows. The analyticsengine may identify and select a particular stream of network packetsfrom the plurality of streams of network packet traversing the packetprocessing device and/or managed by the packet processing device. Theanalytics engine 650 may identify a stream of network packets, from theplurality of streams, corresponding to a flow identifier. The analyticsengine 650 may analyze the identified and/or selected stream of networkpackets traversing the packet processing device 620 and/or beingprocessed by the packet processing engine 240. The analytics engine mayuse a collector 660 to collect metrics on identified streams. Theanalytics engine may store the collected metrics in a stream object. Theanalytics engine may determine, calculate or compute any metricscollected from data or other metrics for an identified stream.

The flow identifier 610 may be any characteristic or attribute thatidentifies or distinguishes a stream of network packets from otherstreams of network packets traversing the device. Examples of flowidentifiers include an internet protocol (IP) address, a uniformresource locator (URL) address, or an application identifier. An IPaddress may be a source address or a destination address. The flowidentifier may comprise an IP address of a client. The flow identifiermay comprise an IP address of a server. In some embodiments, the flowidentifier identifies an IP address of the packet processing device,such as virtual IP address of the VIP server or a mapped IP address usedby an appliance 200. In some embodiments, the flow identifier comprisesan identifier of an application. An application identifier may be anapplication name, a protocol name, an executable name, a host name ofthe application, service name of the application, an applicationcharacteristic, or a protocol characteristic. Characteristics mayinclude port number used, packet header information, packet size, orother packet dimensions. In some embodiments, the flow identifiercomprises a URL. The URL may be a URL requested by the client. The URLmay be a URL served by a server or an application. The URL may identifya portion of a URL, such as a directory.

The analytics engine 650 may have a modifiable configuration or aninterface for receiving configuration and/or commands to direct theoperation of the analytics engine. In some embodiments, an administratoror user can re-configure the analytics engine while the analytic engineis operating. The analytics engine 650 may be configured to select anelement of interest, a client, a URL or an application. The analyticsengine 650 may be configured to identify the maximum number of objectsthat are maintained for an identified stream. In some embodiments, thenumber of objects may be the number of streamed objects. In someembodiments, the number of objects may be the number of data entries orcollection frequency. The analytics engine 650 may be configured todetermine whether to log information to an application flow log or a newlog. The analytics engine 650 may be configured to record and recant thelog frequency. The analytics engine 650 may be configured to identifyhow often to store information to a log—including identifying theinterval. The analytics engine 650 may be configured to sort on anymetric and can sort at runtime. The analytics engine 650 may beconfigured to limit the number of sessions that are returned when a“show stream” function is called. For example, the followingconfigurations can be set for a particular data stream:

maxEntries 500 log NSLOG loginterval 5 sampleCount 4 interval 1 hr sortrequests

An example sample rate can be to maintain 500 objects that are eachsampled at the rate of one object out of every four objects, from whichthe top ‘N’ can be returned (where N can be, e.g., 1-500), and onceevery 5 minutes log the 500 objects into newnslog. The objects that aremaintained may be sorted and stored. The provided result may becompressed to a top number (e.g., N=10) of objects.

The analytics engine 650 provides analytics based on metrics. Forexample, the analytics engine 650 may generate statistics for one ormore of: the number of requests issued, the amount of bandwidth used,the number of connections at any point in time, the frequency with whichrequests are made. In some embodiments, a custom variable may defined oridentified via a configuration interface to the analytics engine.Responsive to the custom variable configuration, the analytics enginemay collect data and metrics on the custom variable in connection withthe identified stream of network packets. Metrics may be related to oneor more identified streams of network packets, such as streams ofnetwork packets from one or clients, streams of network packets to oneor more applications or streams of network packets for one or more URLs.

The collector 660 may comprise an application, program, library,service, process task or any type and form of executable instructionsexecuting on a device such as the packet processing device. Thecollector may be separate to the analytics engine. The collector may bepart of or incorporated into the analytics engine. The analytics engine650 may use the collector to collect the metrics on identified streams.In some embodiments, the collector 660 collects statistics for a streamof network packets. In some embodiments, the collector 660 collectsstatistics for a stream of network packets based on the metrics to bemeasured, such as bandwidth used, response time, number of requests andnumber of connections. The collector 660 may log, record, or store themetrics in memory, on local storage media, or on networked storage.

The analytics engine and/or collector may generate stream objects 715. Astream object may comprise any type and form of object, data structure,data records or file comprising collected and/or calculated metrics. Theanalytics engine and/or collector may generate a stream object for anidentified stream of network packets, such as identified by a flowidentifier. The analytics engine and/or collector may generate a streamobject for each data point or metrics collected for an identified streamof network packets, such as for each frequency of collection of metrics.The analytics engine and/or collector may generate a stream object for aplurality of identified streams of networks packets, such ascorresponding to multiple flow identifiers.

A stream object may comprise information identifying the element(s) ofinterest, such as client, application or URLs. A stream object mayidentify the custom variable and values collected for the customvariable. A stream object may comprise information identifying the flowidentifier. A stream object may comprise information identifying anyinformation about the configuration of the analytics engine for thecollected metrics, such as frequency, number of objects, etc. A streamobject may comprise temporal information on the data points or metricscollected. A stream object may comprise units of measurements for themetrics. A stream object may comprise information identifying formattingof data, such as for display.

In some embodiments, the collector 660 instantiates objects, e.g.,stream objects, to wrap the metrics collected for a stream. In someembodiments, the analytics engine 650, and/or the collector 660, storesmetrics in an instantiated stream object, e.g., by calling a method ofthe object that receives relevant data. Stream objects may be marshaledto other running processes or systems. Stream objects may be marshaledacross a network 104 to a client-side interface device or marshaledacross a network 104′ to a server-side interface device. In someembodiments, an interface device may be a client 102 or a server 106. Insome embodiments, a web interface or client application receives thestream objects for displaying the metrics.

In some embodiments, the generated stream objects include informationrelated to displaying the metrics. For example, the display format mayinclude an IP address or URL for the stream of network packets. In someembodiments, a format is controlled by a request input or configurationparameter, for example, a string specifying the desired format. Forexample, a “?” may indicate that a URL is included in the display, a “*”may indicate that an IP address is in the display, and a “??” or “**”may indicate that both a URL and an IP address are displayed together.

Referring now to FIG. 6B, illustrated is a flow chart of an embodimentof a method of providing analytics on a stream of network packets whilemanaging network traffic between a plurality of clients and one or moreservers. At step 680, a device intermediary to a plurality of clientsand one or more servers manages network traffic between the clients andservers. At step 682, the device identifies a stream of network packetscorresponding to a flow identifier, from a plurality of streams ofnetwork packets traversing the device. At step 684, the device collectsmetrics on the identified stream of network packets. At step 686, thedevice generates one or more stream objects comprising collectedmetrics. At step 688, the device provides one or more stream objectscomprising collected metrics. The device performs each of the steps682-688 while managing network traffic between the plurality of clientsand the one or more servers.

At step 680, the device intermediary to the plurality of clients and theone or more servers managing network traffic between the clients andservers may be the packet processing device 620 illustrated in FIG. 6A.The plurality of clients may be the clients 102 and the one or moreservers may be the servers 106. The packets traversing the packetprocessing device 620 may be received and transmitted via a network 104,104′. The packets may be processed by a packet processing engine 240.While the device is managing network traffic, there is generally aplurality of different streams of network packets traversing the device.The packet processing engine may perform any of the functions andoperations described herein to manage and process network trafficbetween the clients and servers, such as any of the functionallydescribed in FIGS. 2A, 2B and 4C. For example, the packet processingengine may provide SSL VPN 280 functionality, switching 284, DNS 286,acceleration 288 and an app firewall 290. The packet processing enginemay load balance a plurality of services executing on a plurality ofservers.

At step 682, while the device is managing network traffic between theclients and server, the device identifies a stream of network packetscorresponding to a flow identifier. In some embodiments, the flowidentifier is determined or identified based on or responsive to apolicy of a policy engine. In some embodiments, the flow identifier isreceived via a user interface, such as graphical user interface orcommand line interface. In some embodiments, the flow identifier isreceived via a request from a user, such as a request to obtain orgenerate network metrics, such as for a request for a number of request,response time or bandwidth of a client, a URL or an application. In someembodiments, the flow identifier is received via configuration of theanalytics engine by a user, such as an administrator.

The device, e.g., the packet processing device 620 illustrated in FIG.6A., may use an analytics engine 650 or a packet processing engine 240to identify a stream of network packets. The device may identify astream of network packets corresponding to a particular flow identifier.The device may identify a stream of network packets corresponding to achange in traffic, e.g., a new stream of network packets with apreviously unseen flow identifier, where “previously” may beconfigurable to a length of time. The device may identify a stream ofnetwork packets corresponding to flow identifier characteristic, e.g.,an IP address in a range or fitting an IP mask. The device may identifyevery stream of network packets corresponding to flow identifiercharacteristics, e.g., sorting the streams by application names or IPaddresses.

At step 684, while the device is managing network traffic between theclients and server, the device collects metrics on the identified streamof network packets. The device, e.g., the packet processing device 620illustrated in FIG. 6A., may use an analytics engine 650 or a collector660 to collect metrics. As described above, the device may collect, foreach identified stream, one or more of: the number of requests issued,response times for request, the amount of bandwidth used, the number ofconnections at any point in time, the frequency with which requests aremade, and information for a custom variable. In some embodiments, themetrics may be aggregated for multiple identified streams of networkpackets.

At step 686, while the device is managing network traffic between theclients and server, the device generates one or more stream objectscomprising collected metrics. The device may generate multiple streamobjects for each identified stream of network packets corresponding to aflow identifier, such as for the number of objects to collect for thestream. The device may generate a single stream object for eachidentified stream of network packets corresponding to a flow identifier.The device may generate a single stream object for multiple identifiedstream of network packets, such as corresponding to multiple flowidentifiers. For example, a collector 660 may collect statistics for anidentified stream of network packets in memory and generate a streamobject that is stored and may be suitable for transmission to ainterface device that formats and displays the metrics.

At step 688, while the device is managing network traffic between theclients and server, the device provides one or more stream objectscomprising collected metrics. The device may provide the collectedmetrics to a local display, an attached interface device, a networkedinterface device, or a remote networked interface device. In someembodiments the stream objects comprising collected metrics aremarshaled to a compatible system for presentation or storage. In someembodiments, the device provides the stream objects as a web page. Insome embodiments, the device obtains the data stored in the streamobjects and communicates the data via a web page, display the data via auser interface or communicates the data to another device.

Referring now to FIGS. 7A through 7E, an example graphical interface isillustrated that demonstrate some of the capabilities andfunctionalities of the systems and methods disclosed herein. Theinterface illustrated is a web page hosted by a web server and viewed onany device capable of running a web browser and communicating with theweb server. The web server may be hosted by the packet processing device620, a device directly coupled to the packet processing device 620, orat another networked device, e.g., a server 106. The device running theweb browser may be the packet processing device 620, a device directlycoupled to the packet processing device 620, or at another networkeddevice, e.g., a client 102. In some embodiments, the data to bepresented is loaded by a web browser without the use of a web server,e.g., by writing the data to a file directly loadable by the browser.Other display devices and techniques are within the scope of thisdisclosure.

Referring now to FIG. 7A, a display device 700 presents a graphicalinterface 710. The graphical interface 710 presents statistical andanalytical information provided by the packet processing device 620.Information may be shown by flow identifier, e.g., client IP address,application identifier, or destination URL. Information may be shown bymetric, e.g., bandwidth utilization, number of requests, number ofconnections, or response time. In some embodiments, a graphicalrepresentation of the information may be shown, e.g., as a pie chart orbar graph. In some embodiments, the top N flow groups may be shown,e.g., information for the top 5 clients or applications.

Referring now to FIG. 7B, the graphical interface 710 of FIG. 7A isshown with additional references. Features of the interface showninclude a menu bar 720 enabling an interface user to access a pluralityof analytics and device features. For example, a monitoring tab 722 maybe selected to view the monitor displays shown or a configuration tab724 may be selected to access configuration settings for the device.Additional tabs 720 are shown for additional analytics and devicefeatures. The interface illustrated shows information for three of thetop five clients, e.g., because there are only three clients. Client IPaddresses 732 are shown in relation to the bandwidth 734 used by eachclient. For example, as shown, client 10.217.6.13 is using 11,996 KB ofbandwidth. A pie chart 736 is illustrated as a visualization of theproportion of bandwidth consumption attributable to each client.

Referring now to FIG. 7C, a graphical interface 712 is illustrated withtraffic information arranged by uniform resource location (URL) andrequest counts. URLs 742 are shown with a corresponding number ofrequests 744 for each URL. For example, the device has identified 108requests for “/admin_ui/system/application/views/applets”.

Referring now to FIG. 7D, a graphical interface 714 is illustrated withtraffic information arranged in multiple sub-displays, or “widgets”.Each widget displays different data or analytics identified by thedevice. For example, as shown in the illustrated interface 714, thereare three widgets showing application identifiers sorted by requestcounts (e.g., fourteen requests for Oracle), application identifierssorted by bandwidth usage (e.g., 24 KB by Oracle), and applicationidentifiers sorted by response time, in milliseconds (e.g., Oracleresponds in 268 ms, on average). Each widget is illustrated with avisualization of the information, e.g., the widget for applications byresponse time includes a bar graph.

Referring now to FIG. 7E, a graphical interface 716 is illustrated withtraffic information arranged in multiple widgets showing information forclients. Each widget displays different data or analytics identified bythe device. For example, as shown in the illustrated interface 716,there are two widgets showing client IP addresses sorted by requestcounts (e.g., sixty-two requests from 10.216.135.39) and client IPaddresses sorted by bandwidth usage (e.g., 96 KB by 10.216.150.41). Eachwidget is illustrated with a visualization of the information, e.g., apie chart.

It should be understood that the systems described above may providemultiple ones of any or each of those components and these componentsmay be provided on either a standalone machine or, in some embodiments,on multiple machines in a distributed system. The systems and methodsdescribed above may be implemented as a method, apparatus or article ofmanufacture using programming and/or engineering techniques to producesoftware, firmware, hardware, or any combination thereof. In addition,the systems and methods described above may be provided as one or morecomputer-readable programs embodied on or in one or more articles ofmanufacture. The term “article of manufacture” as used herein isintended to encompass code or logic accessible from and embedded in oneor more computer-readable devices, firmware, programmable logic, memorydevices (e.g., EEPROMs, ROMs, PROMs, RAMs, SRAMs, etc.), hardware (e.g.,integrated circuit chip, Field Programmable Gate Array (FPGA),Application Specific Integrated Circuit (ASIC), etc.), electronicdevices, a computer readable non-volatile storage unit (e.g., CD-ROM,floppy disk, hard disk drive, etc.). The article of manufacture may beaccessible from a file server providing access to the computer-readableprograms via a network transmission line, wireless transmission media,signals propagating through space, radio waves, infrared signals, etc.The article of manufacture may be a flash memory card or a magnetictape. The article of manufacture includes hardware logic as well assoftware or programmable code embedded in a computer readable mediumthat is executed by a processor. In general, the computer-readableprograms may be implemented in any programming language, such as LISP,PERL, C, C++, C#, PROLOG, or in any byte code language such as JAVA. Thesoftware programs may be stored on or in one or more articles ofmanufacture as object code.

While various embodiments of the methods and systems have beendescribed, these embodiments are exemplary and in no way limit the scopeof the described methods or systems. Those having skill in the relevantart can effect changes to form and details of the described methods andsystems without departing from the broadest scope of the describedmethods and systems. Thus, the scope of the methods and systemsdescribed herein should not be limited by any of the exemplaryembodiments and should be defined in accordance with the accompanyingclaims and their equivalents.

1. A method for providing, by a device intermediary to a plurality ofclients and one or more servers, analytics on a stream of networkpackets traversing the device while managing network traffic between theplurality of clients and the one or more servers, the method comprising:(a) identifying, by the device while managing network traffic betweenthe plurality of clients and the one or more servers, a stream ofnetwork packets from a plurality of streams of network packets of thenetwork traffic traversing the device and corresponding to a flowidentifier selected from one of: an internet protocol (IP) address, auniform resource locator (URL), and an application identifier; (b)collecting, by the device while managing network traffic between theplurality of clients and the one or more servers, metrics on theidentified stream of network packets; and (c) generating, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, one or more stream objects that comprise thecollected metrics.
 2. The method of claim 1, wherein step (a) furthercomprises receiving, by the device while managing network trafficbetween the plurality of clients and the one or more servers, aselection from a user of one of the IP address, the URL, and theapplication identifier, to analyze one or more metrics.
 3. The method ofclaim 1, wherein step (b) further comprises collecting, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, a plurality of the following metrics: bandwidthutilization, a number of requests, a number of connections and responsetime.
 4. The method of claim 1, wherein step (b) further comprisescollecting, by the device while managing network traffic between theplurality of clients and the one or more servers, for the identifiedstream of network packets a frequency at which requests are made.
 5. Themethod of claim 1, wherein step (c) further comprising storing, by thedevice while managing network traffic between the plurality of clientsand the one or more servers, to the one or more streams objects, anumber of requests issued by the one or more clients via the identifiedstream of network packets.
 6. The method of claim 1, wherein step (c)further comprising storing, by the device while managing network trafficbetween the plurality of clients and the one or more servers, to the oneor more streams objects, a number of requests issued by the one or moreclients via the identified stream of network packets.
 7. The method ofclaim 1, wherein step (c) further comprising storing, by the devicewhile managing network traffic between the plurality of clients and theone or more servers, to the one or more streams objects, a number oftransport layer connections used by the identified stream of networkpackets.
 8. The method of claim 1, wherein step (c) further comprisingstoring, by the device while managing network traffic between theplurality of clients and the one or more servers, to the one or morestreams objects, an amount of bandwidth used by the selected one of theIP address, the URL, and the application, via the identified stream ofnetwork packets.
 9. The method of claim 1, further comprising providing,by the device while managing network traffic between the plurality ofclients and the one or more servers, data from the one or more streamedobjects for displaying metrics for the identified stream of networkpackets.
 10. The method of claim 1, wherein step (b) further comprisescollecting, by the device while managing network traffic between theplurality of clients and the one or more servers, for the identifiedstream of network packets, data for a custom variable and storing thedata for the custom variable to the one or more streamed objects.
 11. Asystem for providing by a device intermediary to a plurality of clientsand one or more servers analytics on a stream of network packetstraversing the device while managing network traffic between theplurality of clients and the one or more servers, the system comprising:a device intermediary to a plurality of clients and one or more servers;an analytics engine executing on the device identifying, while thedevice manages network traffic between the plurality of clients and theone or more servers, a stream of network packets from a plurality ofstreams of network packets of the network traffic traversing the deviceand corresponding to a selected one of an internet protocol (IP)address, a uniform resource locator (URL), or an application identifier;a collector of the analytics engine collecting, while the device managesnetwork traffic between the plurality of clients and the one or moreservers, metrics on the identified stream of network packets; andwherein the analytics engine, while the device manages network trafficbetween the plurality of clients and the one or more servers, generatesone or more stream objects that comprise the collected metrics.
 12. Thesystem of claim 11, wherein the device receives, while managing networktraffic between the plurality of clients and the one or more servers, aselection from a user of one of the IP address, the URL, and theapplication identifier, to analyze one or more metrics.
 13. The systemof claim 11, wherein the collector, while the device manages networktraffic between the plurality of clients and the one or more servers,collects a plurality of the following metrics: bandwidth utilization, anumber of requests, a number of connections, and a response time. 14.The system of claim 11, wherein the collector, while the device managesg network traffic between the plurality of clients and the one or moreservers, for the identified stream of network packets, collects afrequency at which requests are made.
 15. The system of claim 11,wherein the analytics engine stores, while the device manages networktraffic between the plurality of clients and the one or more servers, tothe one or more streams objects, a number of requests issued by the oneor more clients via the identified stream of network packets.
 16. Thesystem of claim 11, wherein the analytics engine stores, while thedevice manages network traffic between the plurality of clients and theone or more servers, to the one or more streams objects, a number ofrequests issued by the one or more clients via the identified stream ofnetwork packets.
 17. The system of claim 11, wherein the analyticsengine stores, while the device manages network traffic between theplurality of clients and the one or more servers, to the one or morestreams objects, a number of transport layer connections used by theidentified stream of network packets.
 18. The system of claim 11,wherein the analytics engine stores, while the device manages networktraffic between the plurality of clients and the one or more servers, tothe one or more streams objects, an amount of bandwidth used by theselected one of the IP address, the uniform resource locator, or theapplication via the identified stream of network packets.
 19. The systemof claim 11, wherein the analytics engine provides, while the devicemanages the device while managing network traffic between the pluralityof clients and the one or more servers, data from the one or morestreamed objects for displaying metrics for the identified stream ofnetwork packets.
 20. The system of claim 11, wherein the collectorcollects, while the device manages network traffic between the pluralityof clients and the one or more servers, for the identified stream ofnetwork packets, data for a custom variable and the analytics enginestores the data for the custom variable to the one or more streamedobjects.